ORIGINAL RESEARCH published: 14 August 2019 doi: 10.3389/fmicb.2019.01855 A Model Based on the Combination of IFN-γ, IP-10, Ferritin and 25-Hydroxyvitamin D for Discriminating Latent From Active Tuberculosis in Children Patricia Comella-del-Barrio 1 , Rosa Abellana 2† , Raquel Villar-Hernández 1 , Mariette Doresca Jean Coute 3 , Beatriz Sallés Mingels 4 , Lydia Canales Aliaga 5 , Margareth Narcisse 3 , Jacqueline Gautier 3 , Carlos Ascaso 2 , Irene Latorre 1 , Edited by: Jose Dominguez 1† and Tomas M. Perez-Porcuna 6* † Xiao-Yong Fan, Fudan University, China 1 Research Institute Germans Trias i Pujol, CIBER Respiratory Diseases, Universitat Autònoma de Barcelona, Badalona, Reviewed by: Spain, 2 Department of Basic Clinical Practice, Faculty of Medicine, University of Barcelona, Barcelona, Spain, 3 John Zaunders, Saint-Damien Pediatric Hospital, Tabarre, Haiti, 4 Radiology and Imaging Diagnose Department, Manso Primary Care St Vincent’s Hospital Sydney, Australia Center, Barcelona, Spain, 5 Radiology Service, Research Unit of the Mútua Terrassa Foundation, University Hospital Mútua Hazel Marguerite Dockrell, Terrassa, Terrassa, Spain, 6 Department of Pediatrics, Tuberculosis and International Health Care Unit, Primary Care and London School of Hygiene & Tropical Mútua Terrassa University Hospital, University of Barcelona, Terrassa, Spain Medicine (LSHTM), United Kingdom Nadia Caccamo, University of Palermo, Italy In recent years, pediatric research on tuberculosis (TB) has focused on addressing *Correspondence: new biomarkers with the potential to be used as immunological non-sputum-based Tomas M. Perez-Porcuna methods for the diagnosis of TB in children. The aim of this study was to characterize tomas.perez.porcuna@gmail.com a set of cytokines and a series of individual factors (ferritin, 25-hydroxyvitamin D † Co-senior authors [25(OH)D], parasite infections, and nutritional status) to assess different patterns for Specialty section: discriminating between active TB and latent TB infection (LTBI) in children. The levels of This article was submitted to 13 cytokines in QuantiFERON-TB Gold In-Tube (QFT-GIT) supernatants were analyzed Infectious Diseases, a section of the journal in 166 children: 74 with active TB, 37 with LTBI, and 55 uninfected controls. All cytokines Frontiers in Microbiology were quantified using Luminex or ELISA. Ferritin and 25(OH)D were also evaluated using Received: 13 December 2018 CLIA, and Toxocara canis Ig-G antibodies were detected with a commercial ELISA kit. Accepted: 29 July 2019 The combination of IP-10, IFN-γ, ferritin, and 25(OH)D achieved the best diagnostic Published: 14 August 2019 performance to discriminate between active TB and LTBI cases in children in relation to Citation: Comella-del-Barrio P, Abellana R, the area under receiver operating characteristic (ROC) curve 0.955 (confidence interval Villar-Hernández R, Jean Coute MD, 95%: 0.91–1.00), achieving optimal sensitivity and specificity for the development of a Sallés Mingels B, Canales Aliaga L, Narcisse M, Gautier J, Ascaso C, new test (93.2 and 90.0%, respectively). Children with TB showed higher ferritin levels Latorre I, Dominguez J and and an inverse correlation between 25(OH)D and IFN-γ levels. The model proposed Perez-Porcuna TM (2019) A Model includes a combination of biomarkers for discriminating between active TB and LTBI Based on the Combination of IFN-γ , IP-10, Ferritin and 25-Hydroxyvitamin in children to improve the accuracy of TB diagnosis in children. This combination of D for Discriminating Latent From biomarkers might have potential for identifying the onset of primary TB in children. Active Tuberculosis in Children. Front. Microbiol. 10:1855. Keywords: pediatrics, biomarkers, immune response, vitamin D, ferritin, enzyme-linked immunoassays, doi: 10.3389/fmicb.2019.01855 Mycobacterium tuberculosis, cytokines Frontiers in Microbiology | www.frontiersin.org 1 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB INTRODUCTION In addition, the impact of alterations in iron homeostasis and vitamin D deficiencies highlight profound effects on immune At least one-quarter of the world’s population is infected function and host defenses due to mechanisms that have not with Mycobacterium tuberculosis (World Health Organization yet been resolved. Lastly, comorbidities by helminth infections [WHO], 2018a). Childhood tuberculosis (TB) represents at least impair the inflammatory and immune mechanisms involved in 10% of the burden of the disease worldwide, being one of the the control of M. tuberculosis infection (Ibrahim et al., 2017). most significant causes of childhood morbidity and mortality In recent years, pediatric research has focused on finding new (World Health Organization [WHO], 2018b). Estimations show biomarkers in non-sputum-based samples for the detection of that there are far more children with TB globally than previously M. tuberculosis infection (Nicol et al., 2015). Current studies thought, with the majority being undiagnosed and untreated have highlighted the importance of diverse forms of biomarkers (Dodd et al., 2017). Underdiagnosis in children can occur for with the potential to be used in immunological methods for the multiple reasons, such as the lack of a non-specific clinical diagnosis of childhood TB (Togun et al., 2018). Furthermore, presentation that delays seeking healthcare and diagnostic there is increasing data showing that modified interferon gamma suspicion; the lack of a more accurate diagnostic test; and poor release assays (IGRAs) based on the analysis of a combination of geographical and financial access to healthcare in some areas different markers could enhance the diagnostic accuracy (Chegou (Kyu et al., 2018; World Health Organization [WHO], 2018a). et al., 2014). However, only a few studies with small cohorts Infants and young children have a higher risk of progressing have identified some cytokine responses in QuantiFERON-TB to TB following a primary M. tuberculosis infection, usually Gold In-Tube (QFT-GIT, QIAGEN, Germany) supernatants due to a child being exposed to an infectious adult with active which have the potential to monitor specific immunity against TB (Augustynowicz-Kopeć et al., 2012) and to the development M. tuberculosis as candidate combinations of markers for the of severe forms of the disease (Marais et al., 2004). Therefore, discrimination between LTBI and active TB in children (Togun household detection of index TB cases, together with early et al., 2018). Despite these initial approaches, a clear pattern detection of the infection and TB disease, followed by a prompt has not yet emerged, and the diagnostic performance of the treatment, are fundamental in preventing disease progression cytokine biomarkers reported do not meet the minimum targets (Dodd et al., 2018). recommended by the WHO for a new diagnostic or triage test for The diagnosis of pulmonary TB is a significant challenge TB in children (World Health Organization, 2017). in children due to the paucibacillary nature of the disease To our knowledge, no cytokine biomarkers based on QFT-GIT and the difficulties in expectorating. Although rapid molecular supernatants combined with individual factors can distinguish diagnosis represents a significant advance as an alternative to between active TB and LTBI in children. To improve the conventional microscopy and culture methods, its sensitivity accuracy of the diagnosis of TB, the aim of this study was to remains unacceptably low in children since the technique is based characterize a set of cytokines and a series of individual factors on detecting M. tuberculosis from respiratory specimens (World (ferritin, 25-hydroxyvitamin D [25(OH)D], parasite infections, Health Organization [WHO], 2018b). As for immunodiagnostic and nutritional status) and to assess different patterns for assays, both the tuberculin-skin-test (TST) and interferon- distinguishing between active TB and LTBI in children. gamma release assays (IGRAs)—that measure cell-mediated immune responses following M. tuberculosis infection—are unable to distinguish between active TB and LTBI (Latorre and MATERIALS AND METHODS Domínguez, 2015) and limit the accuracy of M. tuberculosis detection (Dominguez et al., 2009; Velasco-Arnaiz et al., 2018). Study Population As a result, most active TB cases are diagnosed through A prospective case-control study was conducted from August clinical—and radiological when possible—scoring systems which 2015 to December 2016 in the pediatric hospital of Saint have limitations due to the clinical presentation of the disease Damien in Port-au-Prince (Haiti). Children (0–14 years old) (Graham et al., 2015). who presented signs and symptoms compatible with active TB The immature immune system of young children added to and/or documented TB exposure were screened for suspected the dynamic process of the host–pathogen interaction from TB. According to the hospital program, siblings (0–14 years M. tuberculosis infection, hamper defining the transition from old) of the children diagnosed with TB were also screened latent infection to acute TB disease in children. Recently, a for TB or LTBI. Children (0–14 years old) from a school diversity of genetic and individual factors that may contribute and a kindergarten were screened as uninfected controls. The to the outcome of the host immune set-points during exclusion criteria were: children with known immunodeficiency, M. tuberculosis infection have been described (Bastos et al., on current immunosuppressive treatment, with a condition that 2018). A good understanding of the diversity of these factors could potentially compromise the immune system (e.g., children might be crucial to assess the impact of the host-pathogen from oncology, rheumatology, nephrology and those who had interactions that occur during M. tuberculosis infection. In this undergone organ transplantation), children who had been under sense, the WHO guidelines for the management of malnourished anti-TB treatment or preventive treatment during the previous children, as well as guidelines for national TB programs, year, and children not providing informed consent. underline the importance of the association of malnutrition and The following information was collected: age, sex, weight, TB in children (World Health Organization [WHO], 2013). height, previous medical history (including TB history, Frontiers in Microbiology | www.frontiersin.org 2 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB TB exposure, HIV status, and comorbidities, hemogram), differentiated into those with pulmonary involvement (PTB) vaccines, and current and previous medication (antibiotics, and children with isolated mediastinal lymphadenopathy in the corticosteroids, antiparasitic drugs). absence of lung parenchyma involvement (Mediastinal TB). LTBI The following signs and symptoms were evaluated: cough cases were defined as children with documented TB exposure, and/or fever ≥2 weeks (with no improvement after at least a positive TST and/or QFT-GIT, normal chest radiographs, and 7-day course of amoxicillin), recent unexplained weight loss, no clinical signs of TB development in the last 6 months and asthenia/fatigue. The TST was performed by a trained after diagnosis. Finally, uninfected controls were defined as laboratory technician. Intradermal injection of 0.1 ml of Tubersol asymptomatic children with no history of TB exposure, and (bioequivalent to 5 tuberculin units; Sanofi Pasteur, Toronto, ON, negative TST and QFT-GIT. Canada) was placed into the ventral surface of the lower arm and read after 72 h. A positive TST result was defined as an Laboratory Tests Performed induration ≥10 mm in BCG-vaccinated children (those with a Molecular Diagnostic Test BCG scar), and ≥5 mm in non-BCG-vaccinated children or with Sputum samples were collected from children with microscopy a known adult TB contact (Bass et al., 1990; American Academy confirmation and/or radiological findings to perform of Pediatrics Tuberculosis, 2009). A standardized specific Z- score GeneXpert MTB/RIF (Cepheid, United States) according to for detection of nutritional status weight-for-age (WAZ) was the manufacturer’s instructions. determined by WHO Anthro Plus 1.0.4 software (World Health Organization [WHO], 2009). Children with WAZ scores below QuantiFERON-TB Gold In-Tube −2 standard deviation (SD) were defined as underweight, and a In all the participants, a 3 ml blood sample was drawn for WAZ score above 2 SD was defined as overweight. conventional QFT-GIT; the antigen tube (ESAT-6, CFP-10, A chest radiograph (anterior–posterior image) was performed and TB-7.7), and positive (phytohemagglutinin, mitogen) and in all the children screened for TB or LTBI. Chest radiographs negative (no antigen, nil) controls. Tubes were incubated at 37◦ C were read by two external experts who were blinded to clinical for 16–24 h and centrifuged according to the manufacturer’s data using a standardized reporting form and a third reader to instructions. Plasma was harvested and stored at −20◦ C until resolve discordant opinions (Graham et al., 2015). In addition, performing the enzyme-linked immunosorbent assay (ELISA). nasopharyngeal aspirates and induced sputum were collected After the screening and recruitment of cases, plasma samples on three consecutive days for smear examination (auramine were sent to the laboratories of the Research Institute Germans stain) by direct fluorescence microscopy in children suspected Trias i Pujol (IGTP, Badalona, Spain) following optimum of having active TB. Histological examination was performed in conservation conditions. Once there, the supernatants were children with suspicion of extrathoracic TB (ETB) with lymph analyzed and the results were interpreted according to the node adenopathies. manufacturer’s instructions. Of all the children screened for TB or LTBI, only those with a positive TST result and/or microscopic confirmation were invited Ferritin, 25(OH)D, and Toxocara spp. Detection to participate in the study. Of all the children screened in the One milliliter of blood from all the participants was added to schools, only those with a negative TST result were invited to the biochemical tube to perform ferritin, 25(OH)D, and Toxocara participate in the study as uninfected controls. canis determination. Ferritin and 25(OH)D concentrations were Treatment and preventive treatment were prescribed in all analyzed at the biochemistry laboratory of the Germans Trias the children diagnosed with TB or LTBI, respectively. During i Pujol Hospital (Badalona, Spain) with a Chemiluminescence TB treatment and preventive treatment, the patients were Immunoassay (CLIA) method using a Liaison instrument followed monthly until the end of treatment. Children with (DiaSorin Liaison, Stillwater, MN, United States). 25(OH)D a positive sputum smear were retested at the fifth and sixth is an indirect method to measure vitamin D in the blood. month of treatment. According to the literature, serum 25(OH)D levels equal or above 20 ng/ml were considered normal levels of vitamin D (Michael and Holick, 2007). To avoid variations during blood Definitions for Classification of the sampling, the blood was almost always collected on the same Children Enrolled in the Study day of the week at approximately the same hour (13–15 h). Children were classified according to their clinical history, Seasonal fluctuations did not affect sampling because the weather chest radiographs, smear examination, molecular diagnostic test, seasons in Haiti are barely defined. T. canis Ig-G antibodies TST and QFT-GIT results. Active TB cases were defined as were detected at the IGTP laboratory using a commercial ELISA confirmed TB —children with relevant signs and symptoms kit (Ridascreen, R-Biopharm AG, Germany). Results with a and microbiologic confirmation of M. tuberculosis—, and sample index above 1.1 were considered positive according to the unconfirmed TB —children without bacteriological confirmation manufacturer’s instructions. but with relevant signs and symptoms, positive TST and/or QFT-GIT, radiological findings suggestive of TB, known TB Detection of Soil-Transmitted Parasite Infections contact, and clinical response to anti-TB treatment. Depending Stool samples were collected to detect intestinal parasites in on the TB location, active TB cases were classified as ETB all the participants. Stool samples were processed on the or intrathoracic TB. Children with intrathoracic TB were same day of collection at the laboratory of the pediatric Frontiers in Microbiology | www.frontiersin.org 3 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB hospital of Saint Damien using the Kato-Katz and formalin– were expressed using the odds ratios (OR) and their confidence gasoline technique (a modification of the formalin-ether intervals. Sensitivity and specificity were calculated for assessing sedimentation technique) as described previously (Katz et al., the value of performing a diagnostic test. The receiving operating 1972; Ahmadi and Damraj, 2009) and were examined with characteristic (ROC) curve was used to evaluate diagnostic optical microscopy. accuracy. The optimal cut-off value was identified to maximize the difference between true positive and false positives subjects. Cytokine Measurement The level of significance was set at 0.05. Frozen supernatants remaining from the QFT-GIT tubes were These analyses were performed using the statistical software used for the measurement of cytokine concentrations using a IBM SPSS Statistics v. 25 (SPSS, Chicago, IL, United States), R bead-based multiplex assay (Luminex 11-plex cytokine kit, R&D package v.3.0.5 (R Foundation for Statistical Computing, Vienna, Systems, United Kingdom) and measured by Bioplex manager Austria), and GraphPad PRISM v. 5 (GraphPad Software, Inc., software (version 5.0, Bio-Rad, United States) according to San Diego, CA, United States). the manufacturer’s instructions. After optimization experiments, granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon (IFN)-gamma (γ), interleukin (IL)-2, IL-5, IL-10, RESULTS IL-13, IL-22, IL-17, and tumor necrosis factor (TNF)-alpha (α) were analyzed in a 1:8-fold dilution, while IL-1RA and Study Subjects induced protein (IP)-10 were analyzed in 1:8, 1:80, and 1:160-fold A total of 305 children suspected of having LTBI or TB were dilutions. In this way, values were within the detection limits screened in the hospital, whereas a total of 96 uninfected children marked in the standard curve. IL-32 and vascular endothelial were screened in a school and a kindergarten. Among the growth factor (VEGF) were measured by DuoSet ELISA (R&D patients screened at the hospital, 156 were recruited, and 149 Systems, United Kingdom) because of incompatibilities with the were excluded because they did not meet the inclusion criteria human custom multiplex cytokine kit. ELISA was performed (informed consent not obtained, negative TST). Of the 156 according to the manufacturer’s instructions. participants, 111 (71.2%) were analyzed in the study, and 45 (28,8%) were lost to follow-up and were therefore not included Statistical Analysis in the analysis due to lack of complementary tests necessary Qualitative variables were described using frequencies and for clinical assessment (chest radiographs, biopsies). Among the percentages. Qualitative variables were described using children screened at school and kindergarten, 55 were recruited median and interquartile ranges (IQR), or, using mean and and analyzed, and 41were excluded because they did not meet the standard deviation (SD) in case of variables were with a inclusion criteria (informed consent not obtained, positive TST). normally distribution, using mean and standard deviation. The Among the 166 children analyzed (111 screened at the hospital independent variables analyzed were: sex, age, weight by age, and 55 screened at school and kindergarten), 74 had active TB BCG, hemoglobin levels, 25(OH)D levels, ferritin levels, the (44.6%), 37 had LTBI (22.3%), and 55 were uninfected (33.1%). presence of intestinal helminths, IgG T. canis antibodies, and Of the 74 active TB cases, 8 had ETB, and 66 had intrathoracic cytokines responses. The concentration of released cytokines TB. Among the intrathoracic TB children, 48 had PTB, and 18 released in response to M. tuberculosis antigens (Ag-TB) and had Mediastinal TB (Figure 1). phytohemagglutinin (PHA) was calculated by subtracting the Table 1 shows the description, demographic, and clinical concentration measured in the nil tube (Ag-TB, antigen minus characteristics among study groups according to their QFT-GIT nil; and PHA, mitogen minus nil). For all the variables with a result. Significant differences were observed in age and body normal distribution, the comparison between several groups was WAZ z-scores (p = 0.001 and p = 0.001, respectively) among performed using the analysis of variance or Student’s t-student the study groups with different QFT-GIT results (positive, test (only two groups). However, for variables non-normally negative, and indeterminate). Whereas LTBI cases with positive distributed variables, the comparison between groups was QFT-GIT were older than active TB cases with negative QFT-GIT performed using Kruskal–Wallis and Mann–Whitney tests. In (p = 0.002), active TB cases with positive QFT-GIT had lower the case of qualitative variables, comparisons were performed WAZ z-scores than uninfected controls (p = 0.001). However, using the Fisher’s exact test or chi-squared test. The Tukey comparisons among QFT-GIT results within each study group method (normal distribution) or Benjamini and Hochberg (TB, LTBI, and non-infected) were performed, and no significant method (non-normal distribution) was used to correct p-values differences were observed. in multiple comparisons. The cytokines that showed significant differences between study groups were evaluated and considered. Characterization of Subjects With a Multivariate logistic regression was performed to detect Positive QFT-GIT Test variables able to classify individuals among the three different Comparisons between the groups with active TB and positive study groups (active TB, LTBI, and uninfected). The forward QFT-GIT were performed (Table 2). The Ag-TB levels of IL-17A, method was used for selecting the best combinations of cytokines. GM-CSF, together with the PHA levels of TNF-α, GM-CSF Participants with a positive QFT-GIT result (TB and LTBI) were and, IL-13, and median hemoglobin levels showed significant analyzed separately (Binomial) from those with a negative QFT- differences between active TB groups (p = 0.009, p = 0.027, GIT result (TB, LTBI, and uninfected; Multinomial). The results p = 0.027, p = 0.040 and p = 0.042, p = 0.006, respectively). Frontiers in Microbiology | www.frontiersin.org 4 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB FIGURE 1 | Flow diagram of enrollment. TB, tuberculosis; LTBI, latent tuberculosis infection; ETB, extrathoracic TB; PTB, intrathoracic TB with pulmonary involvement; Mediastinal TB, intrathoracic TB with isolated mediastinal lymphadenopathy in the absence of lung parenchyma involvement. Furthermore, pairwise comparisons showed that Ag-TB levels of children had an eosinophil count, this variable was not included IL-17A and GM-CSF, together with the PHA levels of TNF-α in the analysis of the study. Despite the few results, no significant and IL-13, were higher in children with Mediastinal TB than in differences were found between Ag-TB, PHA and nil IL-5 levels those with PTB (p = 0.009 and 0.042, p = 0.025 and p = 0.050, and eosinophil count in the groups with a positive QFT-GIT respectively). Likewise, hemoglobin levels were significantly (p-values of 0.848, 0.923, and 0.768, respectively). higher in children with Mediastinal TB than in children with PTB or ETB (p = 0.014 and p = 0.014, respectively). No biomarker showed significant differences between the PTB and ETB groups. Characterization of Subjects With a Therefore, the groups of children with PTB and extrapulmonary Negative QFT-GIT Test TB were merged and analyzed as a single group (TB, n = 44), while Comparisons among active TB cases (n = 9), LTBI cases children with Mediastinal TB (n = 18) were analyzed separately. (n = 12) and uninfected controls (n = 55) with a negative Comparisons between the TB group (n = 44) and LTBI cases QFT-GIT (n = 22) were performed (Table 4). The PHA levels with a positive QFT-GIT (n = 22) were performed (Table 3). The of IL-10, IL-13, and IL-32, together with the nil levels of Ag-TB levels of IP-10 along with ferritin levels were significantly TNF-α and IL-10, the underweight levels, and 25(OH)D levels higher in children with TB than in children with LTBI (p = 0.005 showed significant differences (p < 0.001, p = 0.007, and and p = 0.019, respectively). However, the PHA levels of IFN-γ p = 0.004, p = 0.001 and p = 0.044, p = 0.001, and p = 0.037, were significantly lower in children with TB than in those with respectively). Furthermore, pairwise comparisons showed that LTBI (p < 0.001). Although nil levels of IL-5 showed significant PHA levels of IL-10 were significantly higher in TB and LTBI differences between groups (p = 0.007), this cytokine was not cases than in uninfected controls (p = 0.020 and p = 0.001, considered in the analysis because almost all the results of respectively), whereas the PHA levels of IL-32 were significantly the LTBI cases (20/22) and more than half of those of the higher in LTBI cases than in TB cases, and uninfected controls children who belonged to the TB group (24/44) were below the (p = 0.034 and p = 0.004, respectively), and the PHA levels standard curve. Regarding the association of T. canis with IL-5, of IL-13 were significantly higher in LTBI cases compared to no significant differences were found between Ag-TB, PHA and uninfected controls (p = 0.006). Otherwise, the nil TNF-α levels nil IL-5 levels and T. canis in the groups with positive QFT-GIT were significantly higher in uninfected controls compared to (p-values of 0.202, 0.508, and 0.053, respectively). Moreover, the LTBI cases (p < 0.001). Regarding levels of malnourishment, eosinophil count was determined, but because only 25% of the the WAZ z-scores were significantly lower in TB and LTBI Frontiers in Microbiology | www.frontiersin.org 5 August 2019 | Volume 10 | Article 1855 Frontiers in Microbiology | www.frontiersin.org Comella-del-Barrio et al. TABLE 1 | Description and comparison of the demographic and clinical characteristics among the study groups according to QFT-GIT results. Study groups classified by QFT-GIT result (n = 166) Active TB (n = 74) LTBI (n = 37) Uninfected (n = 55) p. overall Positive Negative Indeterminate Positive Negative Indeterminate Negative n = 62 n=9 n=3 n = 22 n = 12 n=3 n = 55 Gender 0.548 Female 26 (41.9%) 5 (55.6%) 2 (66.7%) 12 (54.5%) 6 (50.0%) 3 (100%) 25 (45.5%) Male 36 (58.1%) 4 (44.4%) 1 (33.3%) 10 (45.5%) 6 (50.0%) 0 (0%) 30 (54.5%) Age in years 85.3 (44.8) 47.3 (51.6) 59.0 (32.0)a 114 (45.6)a 80.6 (44.6) 48.7 (19.5) 76.5 (35.2) 0.001 6 Range 0.008 <5 years 25 (40.3%) 7 (77.8%) 2 (66.7%) 5 (22.7%) 6 (50.0%) 3 (100%) 32 (58.2%) >5 years 37 (59.7%) 2 (22.2%) 1 (33.3%) 17 (77.3%) 6 (50.0%) 0 (0%) 23 (41.8%) Body weight-for-age Z-score (SD) −1.39 (1.70)a −1.70 (1.09) −1.78 (1.06) −0.66 (0.98) −1.57 (1.50) −0.92 (1.23) −0.30 (1.00)a 0.001 BCG scar 0.424 Yes 41 (69.5%) 7 (87.5%) 2 (66.7%) 15 (71.4%) 9 (100%) 1 (50.0%) 39 (72.2%) Hemoglobin (g/dl) 10.4 (2.02) 9.89 (0.97) 9.57 (0.84) 11.2 (1.30) 11.0 (1.37) 11.0 (3.33) 11.5 (0.66) 0.457 Categorical variables are expressed as frequencies (n) and percentages (%), and quantitative variables are expressed as median and interquartile ranges (IQR) or standard deviation (SD). Statistical differences between pairwise comparisons (a). QFT-GIT, QuantiFERON-TB Gold In-Tube; TB, tuberculosis; LTBI, latent tuberculosis infection; Z-score, default classification system used to present child nutritional status; BCG, Bacillus Calmette-Guérin. Bold values, statistical significative values with a p-value under 0.05. Biomarkers for Diagnosing Pediatric TB August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB TABLE 2 | Description and comparison of demographic, clinical, and cytokine responses among active TB cases with positive QFT-GIT. Study subjects with active TB and a positive QFT-GIT assay classified by disease location (n = 62) PTB ETB Mediastinal TB p. overall n = 36 n=8 n = 18 Gender 0.935 Male 20 (55.6%) 5 (62.5%) 11 (61.1%) Age in years 76.0 [34.5; 115] 89.5 [55.5; 100] 99.0 [70.2; 130] 0.187 Range 0.406 <5 years 17 (47.2%) 3 (37.5%) 5 (27.8%) >5 years 19 (52.8%) 5 (62.5%) 13 (72.2%) Body weight-for-age Z-score −1.24 [−2.74; 0.08] −2.07 [−2.79; −1.13] −0.98 [−2.37; −0.21] 0.334 BCG scar 0.854 Yes 23 (69.7%) 5 (62.5%) 13 (72.2%) Hemoglobin (g/dl) 10.3 [8.90; 11.6]a 9.00 [8.15; 10.9]b 12.0 [10.8; 12.1]ab 0.006 Intestinal parasites Protozoa (cyst) 0 (0%) 0 (0%) 2 (33.3%) 0.308 Helminths (ova) 0 (0%) 1 (33.3%) 0 (0%) 0.120 Serology Toxocara spp. 0.099 Negative 31 (86.1%) 5 (62.5%) 11 (64.7%) Positive 5 (13.9%) 3 (37.5%) 6 (35.3%) Ferritin (ng/ml) 98.4 [33.0; 201] 138 [78.5; 218] 64.4 [47.4; 117] 0.276 25 (OH) D(ng/ml) 26.6 [20.6; 34.5] 30.2 [26.3; 34.2] 28.6 [21.8; 31.2] 0.735 Range 1.000 Normal levels 27 (75.0%) 6 (75.0%) 14 (77.8%) Deficiency 9 (25.0%) 2 (25.0%) 4 (22.2%) Cytokine response (pg/ml) Ag-TB TNF-α 105 [−46.08; 399] 53.1 [36.3; 248] 136 [66.2; 386] 0.400 IP-10 31153 [12825; 47686] 37425 [10304; 57206] 33127 [29369; 48717] 0.778 IL-10 39.5 [23.9; 59.3] 36.4 [16.9; 56.7] 52.4 [47.2; 62.0] 0.060 IFN-γ 3922 [1150; 10449] 3855 [2957; 6969] 7020 [4866; 13847] 0.200 IL-1RA 27796 [12141; 42882] 25015 [13848; 66213] 23673 [15354; 51940] 0.928 IL-17A 7.58 [1.51; 12.6]a 5.67 [0.00;19.2] 23.1 [9.13; 35.9]a 0.009 GM-CSF 41.4 [8.04; 97.1]a 28.9 [11.5; 54.8]b 83.6 [39.6; 201]ab 0.027 IL-13 716 [315; 1350] 1342 [534; 1876] 1326 [984; 1755] 0.071 IL-5 3.32 [0.00; 7.05] 0.00 [0.00; 13.5] 8.59 [3.53; 25.7] 0.204 IL-32 30.1 [−122.86; 64.1] 59.4 [−25.44; 396] 77.1 [−10.03; 360] 0.222 VEGF −381.77 [−784.77; −120.49] −903.69 [−1128.04; −499.36] −468.37 [−931.27; −173.86] 0.150 PHA TNF-α 4961 [2833; 8837]a 4850 [3446; 7646] 9762 [4829; 12489]a 0.027 IP-10 4718 [2862; 7972] 5335 [2623; 16865] 6952 [814; 19877] 0.840 IL-10 −2.79 [−11.05; 0.00] 0.00 [−0.30; 0.91] 0.00 [−1.99; 0.92] 0.071 IFN-γ 1102 [632; 3913] 1029 [876; 1878] 1828 [1131; 8723] 0.272 IL-1RA 46679 [27310; 80379] 39813 [17196; 46881] 82727 [29720; 142991] 0.311 IL-17A 39.8 [13.4; 129] 9.07 [6.54; 13.1] 19.8 [8.22; 81.8] 0.057 GM-CSF 65.2 [34.1; 118] 26.7 [9.59; 46.5]b 74.7 [54.8; 112]b 0.040 IL-13 1211 [664; 1970]a 1536 [1132; 2023] 2150 [1423; 2608]a 0.042 IL-5 4.28 [0.00; 7.38] 0.00 [0.00; 0.00] 2.98 [0.52; 4.76] 0.064 IL-32 43.9 [−74.11; 243] 7.99 [−98.12; 686] 243 [69.0; 739] 0.109 VEGF −62.75 [−368.65; 228] −434.83 [−559.52; −156.10] −73.02 [−503.76; 517] 0.297 Nil TNF-α 151 [40.3; 250] 33.6 [17.3; 178] 106 [55.3; 209] 0.388 IP-10 673 [412; 1220] 745 [529; 1082] 973 [616; 1201] 0.573 (Continued) Frontiers in Microbiology | www.frontiersin.org 7 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB TABLE 2 | Continued Study subjects with active TB and a positive QFT-GIT assay classified by disease location (n = 62) PTB ETB Mediastinal TB p. overall n = 36 n=8 n = 18 IL-10 8.52 [1.62; 16.3] 0.88 [0.00; 5.10] 5.45 [3.49; 9.86] 0.168 IFN-γ 197 [114; 509] 310 [106; 454] 200 [171; 451] 0.872 IL-1RA 14867 [9160; 22252] 11778 [6783; 27489] 12406 [8385; 20155] 0.765 IL-17A 0.00 [0.00; 11.3] 0.00 [0.00; 0.00] 3.33 [0.00; 19.7] 0.239 GM-CSF 1.92 [0.00; 16.2] 0.00 [0.00; 2.41] 2.67 [0.85; 5.27] 0.414 IL-13 311 [147; 622] 257 [0.00; 423] 341 [292; 444] 0.604 IL-5 0.00 [0.00; 5.88] 0.00 [0.00; 8.95] 3.26 [0.00; 5.52] 0.937 IL-32 1096 [508; 2241] 1606 [699; 2579] 1558 [1101; 2840] 0.376 VEGF 702 [175; 1801] 935 [726; 1128] 693 [368; 1323] 0.830 Categorical variables are expressed as frequencies (n) and percentages (%), and quantitative variables are expressed as median and interquartile ranges (IQR) or standard deviation (SD). Statistical differences between pairwise comparisons (a, b). QFT-GIT, QuantiFERON-TB Gold In-Tube; TB, tuberculosis; PTB, Intrathoracic TB with pulmonary involvement; ETB, Extrathoracic TB; Mediastinal TB, Intrathoracic TB with isolated mediastinal lymphadenopathy in the absence of lung parenchyma involvement; Z-score, default classification system used to present child nutritional status; BCG, Bacillus Calmette-Guérin; 25(OH)D, 25-hydroxyvitamin D; Ag-TB, antigen- dependent response; PHA, mitogen-induced response. Bold values, statistical significative values with a p-value under 0.05. TABLE 3 | Description and comparison of demographic, clinical, and cytokine response between groups with a positive QFT-GIT. Subjects with a positive QFT-GIT assay (n = 66) Active TB∗ LTBI p. overall n = 44 n = 22 Body weight-for-age Z-score −1.32 [−.74; −0.17] −0.64 [−1.58; 0.08] 0.061 Intestinal parasites Protozoa (cyst) 0 (0%) 1 (50.0%) 0.200 Helminths (ova) 1 (5.88%) 1 (16.7%) 0.462 Toxocara spp. 0.324 Negative 36 (81.8%) 13 (68.4%) Positive 8 (18.2%) 6 (31.6%) Ferritin(ng/ml) 109 [38.2; 201] 52.2 [32.5; 70.9] 0.019 25 (OH) D(ng/ml) 27.6 [20.8; 34.5] 24.7 [21.2; 30.3] 0.563 Range 0.755 Normal levels 33 (75.0%) 18 (81.8%) Deficiency 11 (25.0%) 4 (18.2%) Cytokine responses (pg/ml) Ag-TB TNF-α 71.0 [−40.32; 364] 47.5 [−26.19; 151] 0.654 IP-10 31545 [12093; 48379] 7762 [3676; 26629] 0.005 IL-10 39.3 [22.1; 59.3] 22.9 [12.1; 44.2] 0.121 IFN-γ 3922 [1201; 10427] 1832 [672; 9569] 0.221 IL-1RA 27796 [12141; 48396] 13918 [4821; 33546] 0.138 IL-17A 7.58 [0.40; 14.9] 10.5 [0.88; 60.2] 0.173 GM-CSF 34.5 [8.04; 97.1] 30.2 [18.4; 60.3] 0.828 IL-13 728 [315; 1468] 427 [171; 1229] 0.118 IL-5 2.90 [0.00; 7.05] 0.00 [0.00; 8.99] 0.579 IL-32 34.7 [−99.73; 72.6] −63.80 [−176.88; 59.4] 0.206 VEGF −442.15 [−913.46; −138.11] −357.76 [−1013.21; −81.31] 0.775 PHA TNF-α 4850 [2833; 8837] 6290 [4103; 9904] 0.226 IP-10 4718 [2680; 9102] 4392 [1800; 8974] 0.644 (Continued) Frontiers in Microbiology | www.frontiersin.org 8 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB TABLE 3 | Continued Subjects with a positive QFT-GIT assay (n = 66) Active TB∗ LTBI p. overall n = 44 n = 22 IL-10 −0.47 [−9.25; 0.00] −5.14 [−8.32; −1.05] 0.307 IFN-γ 1102 [717;2984] 4420 [2137; 11309] <0.001 IL-1RA 42206 [27310; 69517] 45310 [27013; 112972] 0.812 IL-17A 26.0 [9.06; 112] 99.5 [18.9; 229] 0.053 GM-CSF 55.1 [24.4; 103] 79.4 [47.3; 135] 0.121 IL-13 1232 [683; 1973] 1180 [796; 1812] 0.946 IL-5 2.92 [0.00; 6.98] 0.91 [0.00; 10.1] 0.967 IL-32 32.9 [−74.11; 304] −1.83 [−57.38; 75.4] 0.391 VEGF −108.91 [−462.16; 181] −315.24 [−871.29; −16.37] 0.135 Nil TNF-α 139 [35.0; 250] 90.0 [38.0; 185] 0.654 IP-10 680 [423; 1189] 435 [208; 1208] 0.161 IL-10 7.63 [0.19; 14.9] 9.40 [5.28; 13.0] 0.526 IFN-γ 226 [111; 508] 241 [179; 388] 0.523 IL-1RA 14041 [8927; 23001] 11090 [6497; 17128] 0.106 IL-17A 0.00 [0.00; 10.4] 0.00 [0.00; 2.46] 0.764 GM-CSF 0.89 [0.00; 12.3] 0.83 [0.00; 5.30] 0.429 IL-13 302 [114; 595] 256 [146; 499] 0.683 IL-5 0.00 [0.00; 6.96] 0.00 [0.00; 0.00] 0.007 IL-32 1112 [556; 2241] 1726 [1033; 2590] 0.334 VEGF 809 [209; 1610] 688 [317; 1381] 0.870 Categorical variables are expressed as frequencies (n) and percentages (%), and quantitative variables are expressed as median and interquartile ranges (IQR) or standard deviation (SD). QFT-GIT, QuantiFERON-TB Gold In-Tube; TB, tuberculosis; LTBI, latent tuberculosis infection; Z-score, default classification system used to present child nutritional status; BCG, Bacillus Calmette-Guérin; 25(OH)D, 25-hydroxyvitamin D; Ag-TB, antigen-dependent response; PHA, mitogen-induced response. ∗ In this table, children with Mediastinal TB were not included in the active TB cases. Bold values, statistical significative values with a p-value under 0.05. cases than in uninfected controls (p = 0.006 and p = 0.006, the model correctly classified 76.2% of these into the TB group. respectively). On the contrary, the median 25(OH)D levels Supplementary Table 1 summarizes the diagnostic performance were significantly higher in LTBI cases compared to uninfected of the different combination possibilities of the four host-markers controls (p = 0.022). selected in the adjusted logistic model. Discriminative Biomarker Profiles in Discriminative Biomarker Profiles in Subjects With Positive QFT-GIT Subjects With Negative QFT-GIT The adjusted logistic model showed a set of 4 biomarkers able The adjusted logistic model showed a set of 3 biomarkers able to discriminate between active TB and LTBI: ferritin, 25(OH)D, to discriminate among active TB, LTBI, and uninfected controls: IP-10, and IFN-γ (Table 5). IL-10, IL-13, and IL-32 (Table 6). For each increased unit of IL-13 For each increased unit of IFN-γ (in Ag-TB responses), IP-10 and IL-32 (in PHA responses), the odds of being classified as (in Ag-TB and PHA responses), ferritin, and 25(OH)D, the odds LTBI case increased by 1.003 and 1.003, respectively. However, of being classified as a TB case increased by 1.08, 1.80, 1.13, 1.02, for each increased unit of IL-10 (in PHA responses), the odds and 1.22, respectively. However, for each increased unit of IFN-γ of being classified as uninfected control decreased by 0.93 and (in PHA responses), the odds of being classified as a TB case 0.01, respectively. decreased by 0.46. Therefore, the profile to classify a subject with The combination of PHA levels of IL-10, IL-13, and IL-32 TB but not LTBI is that of low IFN-γ levels (in PHA responses) detected 11.1% of active TB cases, 50.0% of LTBI cases, and 96.4% but high IP-10 (in Ag-TB and PHA responses), 25(OH)D, and of uninfected controls. ferritin levels. The model based on the four host-markers mentioned above was able to correctly classify 93.2% of children with TB, and 90.0% DISCUSSION of children with LTBI. In addition, the area under the ROC curve of this model was 0.955 (CI 95%: 0.91 to 1.00), and the positive This study aimed to identify promising markers to discriminate and negative likelihood ratio were 9.32 and 0.08, respectively between active TB and LTBI in children. We obtained a (Figure 2). Furthermore, when Mediastinal TB was included, combination based on IP-10, IFN-γ, ferritin, and 25(OH)D which Frontiers in Microbiology | www.frontiersin.org 9 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB TABLE 4 | Description and comparison of demographic, clinical, and cytokine response between groups with a negative QFT-GIT. Subjects with a Negative QFT-GIT assay (n = 76) Active TB LTBI Uninfected p. overall n=9 n = 12 n = 55 Body weight-for-age Z-score (SD) −1.44 [−2.45; −1.00]a −1.55 [−2.03; −0.58]b −0.59 [−1.08; 0.32]ab 0.001 Intestinal parasites Protozoa (cyst) 0 (0%) 3 (50.0%) 0 (0%) 0.464 Helminths (ova) 0 (0%) 0 (0%) 2 (4.55%) 1.000 Toxocara spp. 0.314 Negative 6 (66.7%) 7 (58.3%) 42 (77.8%) Positive 3 (33.3%) 5 (41.7%) 12 (22.2%) Ferritin (ng/ml) 68.5 [51.0; 84.6] 44.0 [28.4; 77.7] 37.1 [20.3; 55.4] 0.075 25 (OH) D(ng/ml) 29.6 [24.1; 30.1] 30.4 [27.7; 34.4]b 26.5 [24.6; 30.0]b 0.037 Range Deficiency 0 (0%) 0 (0%) 2 (3.84%) Cytokine response (pg/ml) Ag-TB TNF-α −26.62 [−59.20; 4.27] −7.89 [−37.82; 0.51] −57.31 [−321.36; 72.9] 0.385 IP-10 544 [−34.59; 795] 94.6 [49.9; 1332] 219 [85.6; 594] 0.894 IL-10 1.44 [−2.71; 9.21] 3.77 [0.85; 6.40] 0.85 [−1.64; 9.29] 0.918 IFN-γ 88.4 [0.00; 196] 54.4 [−5.32; 239] 23.3 [−2.05; 82.1] 0.525 IL-1RA 4361 [1455; 9833] 3204 [1280; 7608] 3812 [1853; 9435] 0.886 IL-17A 0.00 [0.00; 0.00] 0.00 [−22.20; 6.61] 0.00 [0.00; 1.12] 0.751 GM-CSF 1.45 [−1.10; 5.08] 0.00 [0.00; 1.45] 0.04 [−5.15; 1.52] 0.670 IL-13 361 [67.3; 591] 81.5 [23.5; 565] 56.0 [0.00; 200] 0.240 IL-5 0.00 [−0.46; 0.00] 0.00 [0.00; 0.49] 0.00 [0.00; 1.88] 0.171 IL-32 5.89 [−145.98; 222] 106 [−143.37; 256] −52.81 [−218.53; −6.17] 0.197 VEGF −769.46 [−1673.90; 0.00] −57.79 [−1369.04; 19.9] −243.45 [−466.44; −22.59] 0.295 PHA TNF-α 7244 [2691; 8401] 4609 [2837; 6360] 6932 [5104; 9965] 0.261 IP-10 7177 [4600; 11211] 6415 [5166; 9139] 6524 [3733; 10553] 0.819 IL-10 −8.92 [−13.01; −4.87]a −9.43 [−11.82; −7.98]b −0.43 [−6.29; 0.00]ab < 0.001 IFN-γ 3092 [2179; 4970] 4808 [3212; 9358] 3998 [1897; 7064] 0.536 IL-1RA 72506 [42906; 111675] 148877 [70665; 201214] 68339 [30968; 172755] 0.184 IL-17A 105 [8.75; 180] 131 [80.7; 224] 80.0 [30.4; 216] 0.390 GM-CSF 39.3 [33.8; 99.2] 64.1 [46.6; 93.7] 71.5 [42.6; 143] 0.186 IL-13 1948 [1467; 2146] 2400 [2021; 2978]b 1563 [789; 2236]b 0.007 IL-5 5.24 [0.91; 5.69] 2.99 [0.00; 11.4] 3.42 [1.15; 6.68] 0.789 IL-32 −198.07 [−315.19; −9.88]c 280 [67.2; 367]bc −24.34 [−160.79; 66.4]b 0.004 VEGF 0.00 [−853.06; 782] 0.00 [−780.01; 374] −27.36 [−358.31; 138] 0.703 Nil TNF-α 228 [71.7; 300] 69.5 [40.4; 99.2]b 312 [155; 809]b 0.001 IP-10 938 [301; 1667] 561 [413; 2085] 487 [317; 770] 0.291 IL-10 12.3 [8.92; 27.5] 14.0 [10.1; 16.5] 7.75 [3.59; 16.0] 0.044 IFN-γ 321 [0.00; 862] 255 [67.9; 440] 199 [89.0; 434] 0.911 IL-1RA 11598 [7467; 18694] 10372 [8682; 16165] 13409 [9432; 22543] 0.304 IL-17A 0.00 [0.00; 44.3] 0.00 [0.00; 26.5] 0.00 [0.00; 0.71] 0.220 GM-CSF 4.98 [0.00; 9.43] 0.00 [0.00; 3.76] 1.30 [0.00; 14.6] 0.258 IL-13 1166 [478; 1519] 376 [324; 727] 373 [206; 947] 0.069 IL-5 0.46 [0.00; 4.96] 0.00 [0.00; 2.49] 3.07 [0.00; 5.52] 0.122 IL-32 1242 [1006; 1740] 2020 [1384; 4215] 1532 [657; 3754] 0.332 VEGF 1029 [626; 1674] 1546 [491; 2629] 484 [222; 1189] 0.113 Categorical variables are expressed as frequencies (n) and percentages (%), and quantitative variables are expressed as median and interquartile ranges (IQR) or standard deviation (SD). Statistical differences between pairwise comparisons corrections (a, b, c). QFT-GIT, QuantiFERON-TB Gold In-Tube; TB, tuberculosis; LTBI, latent tuberculosis infection; Z-score, default classification system used to present child nutritional status; BCG, Bacillus Calmette-Guérin; 25(OH)D, 25-hydroxyvitamin D; Ag-TB, antigen-dependent response; PHA, mitogen-induced response. Bold values, statistical significative values with a p-value under 0.05. Frontiers in Microbiology | www.frontiersin.org 10 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB TABLE 5 | Classification table of the model for the study groups with positive TABLE 6 | Classification table for the study groups with negative QFT-GIT results QFT-GIT results and variables included in the equation. and variables included in the equation. Classification table of the Active TB∗ and LTBI cases with positive Classification table of the study groups with negative QFT-GIT results and QFT-GIT results and variables included in the equation variables included in the equation B P-value Odds Ratio [CI 95%] Modela B P-value Odds Ratio [CI 95%] 25 (OH) D (ng/ml) 0.20 0.012 1.22 [1.05; 1.43] Active TB Ferritin (ng/ml) 0.02 0.010 1.02 [1.01; 1.03] PHA (pg/ml) Cytokine response (pg/ml)† Constant −4.67 Ag-TB IL-10 −0.071 0.036 0.93 [0.87; 0.99] IP-10 0.08 0.017 1.08 [1.01; 1.15] IL-13 1.25 × 10−3 0.073 1.01 [1.00; 1.01] INF-γ 0.12 0.064 1.13 [0.99; 1.29] IL-32 3.42 × 10−4 0.751 1.00 [0.99; 1.01] PHA LTBI IP-10 0.59 0.007 1.80 [1.18; 2.75] PHA(pg/ml) INF-γ −0.77 0.008 0.46 [0.26; 0.82] Constant −8.873 Constant −8.67 0.004 IL-10 −0.095 0.009 0.910 [0.85; 0.98] IL-13 3.06 × 10−3 0.001 1.003 [1.001; 1.005] Binomial Logistic Regression. B, regression coefficient; OR, Odds Ratio; CI, Confidence Interval. QFT-GIT, QuantiFERON-TB Gold In-Tube; TB, tuberculosis; IL-32 2.60 × 10−3 0.007 1.003 [1.001; 1.005] LTBI, latent tuberculosis infection; 25(OH)D, 25-hydroxyvitamin D; Ag-TB, antigen- a The reference category is the uninfected control group. Multivariate Logistic dependent response; PHA, mitogen-induced response. ∗ In this table, children Regression. B, regression coefficient; OR, Odds Ratio; CI, Confidence with Mediastinal TB were not included in the active TB cases.† Cytokine levels Interval. QFT-GIT, QuantiFERON-TB Gold In-Tube; TB, tuberculosis; LTBI, latent were multiplied x10. Bold values, statistical significative values with a p-value under tuberculosis infection; PHA, mitogen-induced response. Bold values, statistical 0.05. significative values with a p-value under 0.05. Latorre and Domínguez, 2015; Pai and Behr, 2016). Previous studies showed evidence of the low sensitivity of the IGRAs in individuals with a depressed or immature immune system such as immunosuppressed patients or young children (Latorre et al., 2014). In our study, very low Ag-TB cytokine levels were found in subjects with negative QFT-GIT in comparison with those with a positive QFT-GIT. Therefore, no cytokine or combination of cytokines showed potential for the discrimination between uninfected controls and M. tuberculosis-infected children with a negative QFT-GIT result. This finding is in line with Lighter-Fisher et al., who reported that LTBI children under 5 years old showed negative QFT-GIT results and very low levels of cytokines (Lighter-Fisher et al., 2010). These results corroborate the weakened immune response of young children in protecting against M. tuberculosis and, therefore, their susceptibility to progress to TB disease. Conversely, in the present study, statistically significant differences were found between markers with potential to diagnose TB and to discriminate active TB from LTBI in M. tuberculosis-infected children with a FIGURE 2 | ROC curve of the four markers presented in the model [IFN-γ, positive QFT-GIT result. IP-10, Ferritin, and 25(OH)D] to discriminate between active TB (N = 44) and latent TB infected cases (N = 37) with positive QuantiFERON-TB Gold In-Tube Since children become more susceptible to developing result. AUC, Area under ROC curve. intrathoracic and ETB disease following exposure to M. tuberculosis, several studies have examined the patterns of expression of a variety of biomarkers to understand the progression of intrathoracic and ETB disease in children showed diagnostic potential and a predictive value higher than (Whittaker et al., 2012). Similar to Kumar et al. (2013) in the the minimum target product profiles (TPPs) recommended. present study no marker was able to differentiate between subjects with intrathoracic TB and ETB (Kumar et al., 2013). Cytokines in M. tuberculosis Infection Although mediastinal TB subjects showed an immune profile and Active Disease similar to that of intrathoracic and ETB, five biomarkers (IL-17, Although IGRAs have become a standard method for the GM-CSF, TNF-α, IL-13, and ferritin) showed potential to identify diagnosis of M. tuberculosis infection, IFN-γ alone is unable mediastinal TB subjects in the TB group. Radiographic signs of to discriminate between TB and LTBI (Denkinger et al., 2015; mediastinal TB have been related to the onset of primary TB Frontiers in Microbiology | www.frontiersin.org 11 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB in children (Thomas, 2019). Considering that TB represents peptides to induce interferon (IFN)-g production by both CD4 a dynamic continuum of states in which the dichotomous and CD8 T-cells (Barcellini et al., 2016). The determination of distinction between infection and disease is often difficult to these biomarkers could be performed using the TB1 tube from differentiate (Perez-Velez et al., 2017), the previous cytokines the QFT-Plus assay, since it contains almost the same relatively suggest a potential for detecting M. tuberculosis-infected children long peptides from M. tuberculosis antigens (ESAT-6 y CFP-10) most likely to progress to the disease and/or early stages of TB. to mainly stimulate CD4 + T cells as those used in the QFT-GIT In subjects with a positive QFT-GIT result, IP-10, IFN-γ, assay antigen tube. Although QFT-Plus does not contain the IL-5, and ferritin responses individually showed statistically TB7.7 antigens, it has been shown that the absence of the TB7.7 significant differences between active TB and LTBI. However, the antigen from the QFT-Plus does not significantly impact assay combination of IP-10, IFN-γ, ferritin, and 25(OH)D achieved performance (Theel et al., 2018). the best diagnostic performance to discriminate between active TB and LTBI cases. IP-10 and IFN-γ play an important role in the immune response to M. tuberculosis infection (Chegou et al., Individual Factors in M. tuberculosis 2014). Several studies have described the good performance of Infection and Disease IP-10 when compared or combined with IFN-γ for the diagnosis The mechanism by which host, pathogens and extrinsic factors of TB and the discrimination between TB and LTBI in children, interact as final determinants of disease outcome and TB respectively (Ruhwald et al., 2012; Villar-Hernandez et al., 2017). transmission is an active area of research (Bastos et al., While IP-10 is a chemokine involved in the trafficking and 2018). In this context, we characterized a series of individual stimulation of monocytes and Th1 cells activated in response factors, among which ferritin and 25(OH)D were markers that to inflammatory foci, IFN-γ is essential for the mediation of showed potential for the discrimination between active TB and the adaptive immune response against M. tuberculosis (Ruhwald LTBI in children. et al., 2008). In contrast to IFN-γ, IP-10 induces a robust, specific Iron is an essential cofactor for mycobacteria propagation M. tuberculosis response not influenced by age (Ruhwald et al., during infection (Olakanmi et al., 2000), and successful protective 2012). Indeed, according to previous studies, IP-10 shows the host-immune response (Mainou-Fowler and Brock, 1985). It same kinetics as IFN-γ but at levels up to 10-fold higher (Lighter is known that acute phase proteins stimulate or inhibit their et al., 2009; Ruhwald et al., 2011). production in response to inflammatory processes such as Previous studies in M. tuberculosis-infected adults and infections. In our study, ferritin levels in LTBI cases were children observed variations in cytokine responses after lower than in active TB cases. Previous findings by our group PHA-stimulation (Mueller et al., 2008; Ruhwald et al., 2008, showed lower ferritin levels in children with a positive QFT- 2011; Alsleben et al., 2012; Jeong et al., 2015). In our study, GIT at the onset of M. tuberculosis infection (Pérez-Porcuna PHA levels of IFN-γ were significantly higher in LTBI cases et al., 2014). Similar studies showed higher median ferritin compared to TB cases. Similar findings have been observed in levels in TB adults than in the other study groups (Jacobs M. tuberculosis-infected adults whose blood was stimulated with et al., 2016). A possible explanation for this result is that QFT-GIT peptides (Jeong et al., 2015). Therefore, PHA-induced ferritin is a recognized acute phase protein in iron storage responses were considered to evaluate host immune status for processes and is closely linked to host response in M. tuberculosis the discrimination between TB and LTBI in children. On the (Thom et al., 2012). other hand, in this study, PHA levels of IP-10 were very similar In the present study, no statistically significant differences to those obtained in M. tuberculosis-specific stimulation. In this were found in 25(OH)D alone between study groups. Vitamin regard, Ruhwald et al. (2008) suggested that PHA was a powerful D is a steroid hormone with pleiotropic actions in many body inducer of IFN-γ. However, the same was not observed with tissues and cells, including cells of the immune system (Nair et al., IP-10, with which PHA levels were rather low. 2018). Several studies suggest that 25(OH)D deficiency (below In our study, IL-5 levels in unstimulated samples showed 20 ng/ml) could compromise antibacterial activity and increase statistically significant differences between TB and LTBI cases. the risk of TB disease by preventing the initiation of immune However, this cytokine was not consistently expressed. Studies response mediated by vitamin D (Hewison, 2012). in adults have shown the potential of IL-5 for discriminating The analysis of 25(OH)D in combination with IP-10, between TB and LTBI cases (Won et al., 2017). However, IFN-γ and ferritin was found to be useful to discriminate the diagnostic value of IL-5 in children is relatively unknown between active TB and LTBI cases. We observed an inverse (Armand et al., 2014). correlation between the 25(OH)D and PHA levels of IFN- In this study, cytokines levels were measured from γ in active TB cases in comparison to LTBI cases. In vitro supernatants remaining from QFT-GIT tubes. Recently, studies have demonstrated how vitamin D induces innate QuantiFERON-TB Gold Plus (QFT-Plus), has been introduced R antimicrobial responses and suppresses proinflammatory in the new generation of QFT assay. For this new test there are cytokine responses (Coussens et al., 2012). Likewise, Ragab et al. two TB-specific antigen tubes, called TB1 and TB2. The TB1 (2016) observed a negative association between the addition tube, contains long peptides derived from ESAT-6 and CFP-10 of vitamin D and PHA-induced IFN- γ levels (Nonnecke (for this new test the peptide TB-7.7 has been removed), and it is et al., 2003) suggesting the multiple mechanisms in which designed to induce a specific CD4 T cells response. TB2 contains vitamin D is involved in the protection of the host against both the same long peptides of TB1 and newly designed shorter M. tuberculosis infection. Frontiers in Microbiology | www.frontiersin.org 12 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB Promising Biomarker-Based Diagnostic should be noted that in this case-control study, the sample Tests in Children size, age ranges according to sex and nutritional status were widely represented. However, according to the results obtained, A recent systematic review by Togun et al. (2018) evaluated additional studies are needed to validate the performance biomarkers able to diagnose TB in children. All the studies of the current model in children with other respiratory performed in QFT-GIT supernatants presented at least a infections. The identification of these biomarkers has the same combination of two markers for the discrimination of active technical difficulty as performance of the QFT-GIT assay. TB and LTBI in children, demonstrating the involvement of However, the combination of biomarkers presented in this several mechanisms mediated by different host markers in study might also have a great potential to discriminate between M. tuberculosis infection and disease (Togun et al., 2018). TB and LTBI in children. To this end, future studies should Several studies have suggested that IL-2 and TNF-α may be be conducted validating the identification of the biomarkers reliable cytokines for the discrimination between active TB and proposed in this study in other geographical areas and LTBI cases in children (Lighter-Fisher et al., 2010; Gourgouillon different populations. et al., 2012). However, we did not find any significant differences in TNF-α, and IL-2 responses in unstimulated and stimulated samples were lower than the minimum concentrations detected in the standard curve of the experiment. Although our CONCLUSION findings may not coincide with some mainly previously cited observations, direct comparisons of biomarkers among studies in Our findings suggest the diagnostic potential of the combination children are complex due to population variability, the burden of IFN-γ, IP-10, ferritin and 25(OH)D detected in supernatants of M. tuberculosis presented in the different settings, and age in QFT-GIT tubes for the diagnosis of pediatric TB and variations that could affect the state of maturity of the immune discrimination between TB and LTBI. In addition, these response of the child. markers may be useful for the identification of the onset Regarding the possible use of biomarkers in the field, of primary TB, although future investigations in transversal considering the TPPs recommended by FIND/WHO, the and prospective longitudinal studies are warranted. This sensitivity and specificity achieved by the combination of IFN-γ, study highlights potential markers with optimal diagnostic IP-10, ferritin and 25(OH)D were optimal (Denkinger et al., accuracy for improving the management of TB diagnosis in 2015). In recent years, two case-control studies presented two children. Finally, developing a rapid diagnostic test based on models for the diagnosis of TB in children with minimal TPPs the immunological biomarkers studied would improve the higher than those reached in this study for the development of access of TB services, thereby promoting early diagnosis of a new diagnostic test (Armand et al., 2014; Zhou et al., 2017). pediatric TB and LTBI. However, they were not able to discriminate between active TB and LTBI cases. In our study, the combination of IP-10, IFN-γ, ferritin, and 25(OH)D achieved the best diagnostic performance ETHICS STATEMENT with correct classification of active TB cases (93.2%) and LTBI cases (90.0%). Moreover, this combination of biomarkers This study was approved by the Health Research Ethics correctly classified 76.2% of the mediastinal TB subjects. Lastly, Committee of the University of Barcelona and the Haitian this combination could be a good diagnostic test to confirm active National Ethics Committee (project number IRB00003099). TB (LR+ = 9.32) and a very robust test to rule out cases with Before participation, written informed consent was obtained active TB from cases with LTBI (LR− = 0.08). from the child’s parents or guardian. Limitations and Strengths of the Study One limitation of the studies evaluating diagnostic tests for AUTHOR CONTRIBUTIONS TB in children is the lack of a microbiological gold standard and adequate, validated clinical scoring systems, resulting in PC-d-B, CA, TP-P, RA, and JD conceived and designed the low diagnostic sensitivity in children. In this study, TST study. PC-d-B, MJC, MN, and JG collected the data. PC-d-B, was defined as a criterion for inclusion of the screened TB RV-H, RA, TP-P, IL, LCA, BSM, and JD analyzed and interpreted and LTBI children to improve patient classification. However, the data. PC-d-B, TP-P, RA, JD, and RV-H drafted the the inclusion criterion mentioned above may have affected article. All authors contributed toward data analysis, drafting the specificity of diagnosis of some risk groups with a and revising the paper and agree to be accountable for all vulnerable immune system including malnourished children. aspects of the work. Despite attempting to control most of the risk factors, the vulnerability of the study population and context did not allow evaluation of some factors which may affect the FUNDING immune system (such as cytomegalovirus and allergies). An important strength of this study is the strict criteria for the This work was supported by grants from: (i) the Isolana classification of the study groups (Graham et al., 2015). It Foundation, (ii) the Maria Francisca de Roviralta Foundation Frontiers in Microbiology | www.frontiersin.org 13 August 2019 | Volume 10 | Article 1855 Comella-del-Barrio et al. Biomarkers for Diagnosing Pediatric TB expedient AT/MA 1-19/07/2017, AT/MA 70-27/04/2016, and Foundation, Port-au-Prince, for their unconditional support AT/MA 3-22/10/2014, (iii) the Instituto de Salud Carlos III throughout this research project, and for valuable assistance (PI-16/1912), integrated in the Plan Nacional de I+D+I and care in recruiting the patients for this study. We thank and cofounded by the ISCIII-Subdirección General de Mr. Movil Junior Wilfrid of the Ministère de la Santé Evaluación and the Fondo Europeo de Desarrollo Regional Publique d’Haïti for his help during the household screening (FEDER), (iv) CERCA Program/Generalitat de Catalunya, (v) of children with a household TB contact. Finally, we also el Departament de Salut de la Generalitat de Catalunya, en thank Dr. Jaume Ollé Goig from the ACTMON Association la convocatòria corresponent a l’any 2017 de concessió de for his support to the TB unit of the Saint Damien Hospital subvencions del Pla Estratègic de Recerca i Innovació en Salut that had an indirect positive influence on this project. The (PERIS) 2016-2020 modalitat intesificació professionals de salut funders were not involved in any of the stages of the expedient SLT006/17/144, and (vi) Fundació Recerca i Docència study, from its design to submission of the manuscript Mútua Terrassa. for publication. ACKNOWLEDGMENTS SUPPLEMENTARY MATERIAL We thank the staff (especially Mr. Louis Yves and Ms. Achil The Supplementary Material for this article can be found Nancy, nurses and laboratory technicians) of the pediatric online at: https://www.frontiersin.org/articles/10.3389/fmicb. 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Evaluating the potential of IP-10 and MCP-2 as biomarkers for the of the Creative Commons Attribution License (CC BY). The use, distribution or diagnosis of tuberculosis. Eur. Respir. J. 32, 1607–1615. doi: 10.1183/09031936. reproduction in other forums is permitted, provided the original author(s) and the 00055508 copyright owner(s) are credited and that the original publication in this journal Ruhwald, M., Dominguez, J., Latorre, I., Losi, M., Richeldi, L., Pasticci, M. B., et al. is cited, in accordance with accepted academic practice. No use, distribution or (2011). A multicentre evaluation of the accuracy and performance of IP-10 reproduction is permitted which does not comply with these terms. Frontiers in Microbiology | www.frontiersin.org 15 August 2019 | Volume 10 | Article 1855