Identification of Inflammatory Biomarkers for Pediatric Malarial Anemia Severity Using Novel Statistical Methods

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1 INFECTION AND IMMUNITY, Nov. 2011, p Vol. 79, No /11/$12.00 doi: /iai Copyright 2011, American Society for Microbiology. All Rights Reserved. Identification of Inflammatory Biomarkers for Pediatric Malarial Anemia Severity Using Novel Statistical Methods John M. Ong echa, 1 * Gregory C. Davenport, 2 John M. Vulule, 3 James B. Hittner, 4 and Douglas J. Perkins 1,2 University of New Mexico Laboratories of Parasitic and Viral Diseases, Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya 1 ; Center for Global Health, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, New Mexico 2 ; Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya 3 ; and Department of Psychology, College of Charleston, Charleston, South Carolina 4 Received 1 April 2011/Returned for modification 11 May 2011/Accepted 12 August 2011 Areas where Plasmodium falciparum transmission is holoendemic are characterized by high rates of pediatric severe malarial anemia (SMA) and associated mortality. Although the etiology of SMA is complex and multifactorial, perturbations in inflammatory mediator production play an important role in the pathogenic process. As such, the current study focused on identification of inflammatory biomarkers in children with malarial anemia. Febrile children (3 to 30 months of age) presenting at Siaya District Hospital in western Kenya underwent a complete clinical and hematological evaluation. Children with falciparum malaria and no additional identifiable anemia-promoting coinfections were stratified into three groups: uncomplicated malaria (hemoglobin [Hb] levels of >11.0 g/dl; n 31), non-sma (Hb levels of 6.0 to 10.9 g/dl; n 37), and SMA (Hb levels of <6.0 g/dl; n 80). A Luminex hu25-plex array was used to determine potential biomarkers (i.e., interleukin 1 [IL-1 ], IL-1 receptor antagonist [IL-1Ra], IL-2, IL-2R, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-15, IL-17, tumor necrosis factor alpha [TNF- ], alpha interferon [IFN- ], IFN-, granulocyte-macrophage colony-stimulating factor [GM-CSF], macrophage inflammatory protein 1 alpha [MIP- 1 ], MIP-1, IFN-inducible protein of 10 kda [IP-10], monokine induced by IFN- [MIG], eotaxin, RANTES, and monocyte chemoattractant protein 1 [MCP-1]) in samples obtained prior to any treatment interventions. To determine the strongest biomarkers of anemia, a parsimonious set of predictor variables for Hb was generated by least-angle regression (LAR) analysis, controlling for the confounding effects of age, gender, glucose-6-phosphate dehydrogenase (G6PD) deficiency, and sickle cell trait, followed by multiple linear regression analyses. IL-12p70 and IFN- emerged as positive predictors of Hb, while IL-2R, IL-13, and eotaxin were negatively associated with Hb. The results presented here demonstrate that the IL-12p70/IFN- pathway represents a set of biomarkers that predicts elevated Hb levels in children with falciparum malaria, while activation of the IL-13/eotaxin pathway favors more profound anemia. * Corresponding author. Mailing address: University of New Mexico Laboratories of Parasitic and Viral Diseases, Centre for Global Health Research, Kenya Medical Research Institute, P.O. Box 1578, 40100, Kisumu, Kenya. Phone and fax: michaelongecha@yahoo.com. Published ahead of print on 22 August Malaria due to Plasmodium falciparum infections accounts for a large proportion of the pediatric morbidity and mortality in sub-saharan Africa (50). In addition, P. falciparum infections are a leading cause of pediatric anemia that can culminate in life-threatening severe malarial anemia (SMA) (6, 28). In areas where transmission is holoendemic, SMA primarily manifests in infants and young children, with a peak incidence from 7 to 24 months of age (6). SMA is characterized by dyserythropoiesis and ineffective erythropoiesis (10). Although the etiology of SMA is multifactorial, a number of studies show that the condition results from increased erythrocyte destruction and decreased red blood cell (RBC) production (reviewed in reference 10). Our recent studies in an area of western Kenya where falciparum transmission is holoendemic demonstrated that suppression of erythropoiesis is a primary feature of SMA (49). In areas of malaria holoendemicity, where malaria prevalence is greater than 80% in children 1 to 4 years of age (6), identification of high-risk children who are most likely to develop SMA is of great public health importance. Previous studies suggest that cytokines play a pivotal role in the pathogenesis of malarial anemia (reviewed in reference 11) and that their levels could be used in the diagnosis and/or prognosis of the disease (13). Elevated levels of proinflammatory cytokines, including interleukin 1 (IL-1 ), IL-6, IL-8, IL-23, gamma interferon (IFN- ), and tumor necrosis factor alpha (TNF- ), are associated with enhanced disease severity in human malaria (17, 22, 27, 38). Conversely, decreased levels of additional proinflammatory cytokines, such as IL-12 and IFN-, are associated with enhanced malaria pathogenesis in humans (22, 26, 38, 41). Anti-inflammatory cytokines also play an important role in malarial pathogenesis through their ability to modulate the proinflammatory response. For example, IL-10 levels increase progressively with enhancing severity of childhood malarial anemia and parasite density (38) and are associated with an inability to clear malaria parasitemia (15). Increased circulating levels of IL-1 receptor antagonist (IL-1Ra) are also associated with enhanced malaria disease severity in African children (17, 20), while reduced production of other anti-in- 4674

2 VOL. 79, 2011 BIOMARKERS FOR MALARIAL ANEMIA SEVERITY 4675 flammatory cytokines, such as transforming growth factor beta (TGF- ), correlate with severe malaria (41). Based on the counterregulatory effects of cytokines in the inflammatory milieu, a number of previous studies have shown that the relative expressions of pro- and anti-inflammatory cytokines (i.e., ratios) are important predictors of the development and outcomes of malarial anemia (24, 26, 39, 41). In addition to cytokines, studies from our laboratory and others have demonstrated that pediatric malaria is associated with altered production of -chemokines, including macrophage inflammatory protein 1 alpha (MIP-1 )/CCL3, MIP-1 / CCL4, and RANTES (regulated upon activation, normal T- cell expressed and secreted)/ccl5 (2, 19, 34, 49). Growth factors, such as granulocyte colony-stimulating factor (G-CSF) and granulocyte-macrophage colony-stimulating factor (GM- CSF), and additional chemokines, including eotaxin/ccl11, monokine induced by IFN- (MIG)/CXCL9, and interferoninducible protein 10 (IP-10)/CXCL10, also appear to play an important role in malaria pathogenesis (2, 16, 51). Based on the important roles of cytokines, chemokines, and growth factors in malaria pathogenesis and on previous studies showing that inflammatory mediators may serve as biomarkers for cerebral malaria severity and mortality (2, 16, 20), as well as for malaria outcomes during pregnancy (21, 51), we investigated the potential role of inflammatory mediators as biomarkers in children with malarial anemia. The biomarkers investigated were IL-1, IL-2, IL-4, IL-5, IL-6, IL-7, IL-8, IL-10, IL-12p70, IL-13, IL-15, IL-17, IFN-, IFN-, TNF-, IL-1Ra, IL-2R, GM-CSF, monocyte chemoattractant protein 1 (MCP- 1), MIP-1, MIP-1, IP-10, MIG, eotaxin, RANTES, the IL- 1Ra/IL-1 ratio, and the IL-2R/IL-2 ratio. Selection of this particular biomarker panel was based on available technologies that could concomitantly measure an inclusive group of inflammatory mediators with known or suspected importance in malaria immunology in the context of very low volumes of available blood samples from young, anemic children. To identify the most relevant biomarkers from the expanded set of inflammatory mediators, we utilized novel statistical modeling with least-angle regression (LAR) analysis to determine a parsimonious set of biomarker predictors that was then used in multiple linear regression models to predict hemoglobin (Hb) levels in children with malaria. In addition, since the degree of anemia in children with malaria is highly influenced by commonly identified concomitant infections, including human immunodeficiency virus type 1 (HIV-1) infections (40), bacteremia (5), and helminthic infections (52), all malaria-infected children with these coinfections were excluded from the analyses. (Results of this study were presented in part at the American Society of Tropical Medicine and Hygiene 57th Annual Meeting, New Orleans, LA, December 2008, abstract 936.) MATERIALS AND METHODS Study area. We undertook the current study at Siaya District Hospital (SDH) in Siaya County, Nyanza Province, western Kenya, an area of P. falciparum transmission holoendemicity reporting increased pediatric malarial admissions despite recent interventions (35). SMA is the primary clinical manifestation of severe malaria in children under the age of 5 years, peaking in children 7 to 24 months of age (6). In addition, 85% of children under 3 years of age admitted to SDH s pediatric ward had malarial anemia (MA), which contributed to 53% of all malaria-related deaths (33). The study area and the hematological manifestations of pediatric MA in the study population have been described in detail elsewhere (36). Study population. Children (n 148, 3 to 30 months of age) presenting with acute P. falciparum malaria were recruited into the study at SDH, western Kenya. The children were stratified according to Hb levels into the following categories: uncomplicated malaria (UM; n 31; Hb levels of 11.0 g/dl), non-sma (n 37; Hb levels of 6.0 to 10.9 g/dl), and SMA (n 80; Hb levels of 6.0 g/dl). SMA was defined based on a geographically referenced population using 14,000 Hb measurements in children less than 48 months of age in western Kenya (29). All children were free of severe malaria symptoms, such as hypoglycemia. Since HIV-1 promotes anemia in children with falciparum malaria (40), only HIV-1- negative children were included in the present study. HIV-1 status was determined by two rapid serological antibody tests and HIV-1 proviral DNA PCR tests as previously described (40). Similarly, bacteremic children and those with hookworm infections were excluded from the study. All study participants were also free from cerebral malaria, which is a very rare occurrence in this area of high malaria transmission (6). Children with malaria were treated according to the Ministry of Health, Kenya (MOH), guidelines using artemether-lumefantrine (Coartem) for uncomplicated malaria and intravenous quinine for severe malaria. Supportive care and blood transfusions were administered according to MOH guidelines. All blood samples were obtained prior to antimalarial and/or any other treatment interventions. All parents or legal guardians of the children gave written informed consent before enrollment in the study. The study was approved by the National Ethical Review Committee of the Kenya Medical Research Institute and the Institutional Review Board of the University of New Mexico. Parasitemia determination. Thick and thin peripheral blood smears were prepared from venous blood samples and stained with Giemsa reagent for malaria parasite identification and quantification by microscopy. Asexual malaria parasites were counted against 300 leukocytes, and parasite densities were determined by multiplying the parasite count by the absolute leukocyte counts from an automated hematology analyzer (Beckman Coulter AcT diff2; Beckman Coulter Corporation, Miami, FL). Circulating inflammatory mediator measurements. Venous blood samples (1.0 to 3.0 ml) were immediately centrifuged following collection, and plasma was separated, aliquoted, and stored at 70 C until use. Circulating cytokine levels were determined by a human cytokine 25-plex antibody bead kit (Bio- Source International) according to the manufacturer s instructions. Plates were read on a Luminex 100 system (Luminex Corporation) and analyzed using the Bio-Plex Manager software (Bio-Rad Laboratories). Detection limits for the inflammatory mediators and receptors were as follows: 3 pg/ml for IL-5, IL-6, and IL-8; 4 pg/ml for MIG; 5 pg/ml for IL-1Ra, IL-2R, IL-4, IL-10, IFN-, eotaxin-1, and IP-10; 6 pg/ml for IL-2; 10 pg/ml for IL-7, IL-13, IL-15, IL-17, TNF-, MIP-1, MIP-1, and MCP-1; and 15 pg/ml for IL-1, IL-12p70, IFN-, GM-CSF, and RANTES. Statistical analyses. Comparisons of continuous variables across the three clinical groups (UM, non-sma, and SMA) were conducted using Kruskal-Wallis tests, and where significant differences were obtained, Mann-Whitney U tests were used for pairwise comparisons. Differences in the proportional measurements were determined using Pearson s chi-square ( 2 ) test. In addition, to determine the ability of the inflammatory mediators to predict the primary endpoint (Hb levels), least-angle regression (LAR; /packages/lars/lars.pdf) analysis was performed. LAR is a regression algorithm for high-dimensional data that utilizes a variant of forward stepwise regression to select a parsimonious set of predictors from a large number of possible covariates for efficient prediction of a response variable (12). For each LAR analysis, the best predictors were identified and then entered into a multiple linear regression analysis to predict Hb levels. Moreover, each linear regression was hierarchical in that the potentially confounding effects of age, gender, glucose-6-phosphate dehydrogenase (G6PD) deficiency, and sickle cell trait were controlled for by entering these variables first as a covariate block (block 1). The best LAR predictors were then entered into the regression equation as a second block (block 2). To help ensure the stability of the linear regression coefficients, the maximum number of best predictors selected from each LAR analysis was maintained at a subject-to-predictor ratio of at least 10 to 1. Given this restriction, for the linear regression on the total sample (n 148), the 15 best predictors from the LAR analysis were retained and then examined as predictors in the linear regression. Likewise, for determining predictors of SMA (n 80), the 8 strongest LAR predictors were selected for the multiple linear regression analysis. To gauge the influence of each predictor, we interpreted standardized partial regression coefficients ( -weights) and squared semipartial correlations. -Weights represent the influence of a single predictor on an outcome, controlling for all other predictors. Formally, a -weight indicates how many standard

3 4676 ONG ECHA ET AL. INFECT. IMMUN. TABLE 1. Demographic and clinical characteristics of the study participants a Characteristic deviations of change are expected in the outcome variable when there is a change of 1 standard deviation in the predictor variable (controlling for all other predictors). The squared semipartial correlation represents the unique amount of criterion, or outcome, variance accounted for by a given predictor variable. For all analyses, a P value of was considered statistically significant. RESULTS Demographic and clinical characteristics of the study participants. The demographic and clinical characteristics of the study participants are listed in Table 1. Children in the different clinical categories (UM, non-sma, and SMA) were comparable in age, gender, glucose levels, and axillary temperatures (P for all). As expected based on the a priori classification, Hb concentrations differed across the groups (P 0.001). However, peripheral parasite densities and prevalences of high-density parasitemia (HDP; 10,000 parasites/ l) were comparable across the groups (P and P 0.668, respectively). Lymphocyte and monocyte counts differed across the groups (P and P 0.001, respectively), while granulocyte counts were comparable across the groups (P 0.378). Post hoc analysis revealed that, relative to the UM group, children with SMA had elevated lymphocyte and monocyte counts (P for both). The proportions of children carrying the sickle cell trait differed across the groups (P 0.050), with the SMA group having the lowest prevalence. Inflammatory mediator profiles. The first step for identifying important biomarkers for predicting malarial anemia severity was the measurement of pro- and anti-inflammatory cytokines, chemokines, and growth factors in the 3 groups of children. As shown in Table 2, circulating levels of the proinflammatory cytokines IL-6, IL-12p70, and IL-17 differed significantly across the clinical groups (P 0.003, P 0.016, and P 0.031, respectively). Among the anti-inflammatory cytokines, only IL-4 and IL-10 levels differed significantly across the groups (P and P 0.001, respectively). Circulating levels of IL-2R differed significantly across the groups (P 0.001), as did the IL-2R/IL-2 ratio (P 0.026). Although not statistically significant, levels of both IL-1Ra and IFN- progressively decreased with increasing disease severity (P Value for indicated clinical group of participants UM Non-SMA SMA P value b No. of participants NA Age (mo) 12.0 (8) 9.0 (9) 8.0 (8) c No. (%) of males 14 (45.2) 23 (62.2) 39 (48.8) d Glucose level (mmol/liter) 4.7 (1.5) 5.1 (1.0) 4.9 (1.4) c Temp ( C) 37.0 (1.8) 37.4 (1.7) 37.5 (1.7) c Hemoglobin level (g/dl) 11.0 (1.0) 8.8 (1.1)** 5.0 (1.0)** <0.001 c No. of parasites/ l 48,354 (87,430) 22,615 (49,929) 26,166 (60,703) c No. (%) of participants with HDP ( 10,000/ l) 24 (77.4) 28 (75.7) 56 (70.0) d No. of lymphocytes ( 10 9 / l) 3.7 (3.0) 4.5 (1.6) 6.8 (4.3)** c No. of monocytes ( 10 9 / l) 0.70 (0.5) 0.65 (1.0) 1.10 (1.0)** <0.001 c No. of granulocytes ( 10 9 / l) 7.05 (7.6) 4.45 (1.5) 4.30 (4.0) c No. of participants with sickle cell trait (%) 8 (25.8) 4 (10.8) 7 (8.8) d a The data are the medians (interquartile ranges IQR ) unless stated otherwise. NA, not applicable;, P b Boldface indicates a P value of c Differences were determined using Kruskal-Wallis tests, and where significant differences were observed, pairwise comparisons with the UM group were performed using Mann-Whitney U tests. d Differences were determined using Pearson s chi-square test. and P 0.057, respectively). Examination of chemokines and growth factors revealed that only IP-10 levels differed significantly across the groups (P 0.008). Post hoc comparisons for all of the significant across-group differences are shown in Table 2. Inflammatory mediators as predictors of malarial anemia severity. After determining the profiles of inflammatory mediators in the 3 groups of children, we determined which mediators were the strongest predictors of malarial anemia severity. To accomplish this, we first performed a LAR analysis of the inflammatory mediators (n 25) and biologically relevant ratios (n 2) for the total sample and the SMA group separately. The following inflammatory mediators and ratio emerged as the 15 best predictors of Hb levels in the total sample (listed in order of predictive strength): IL-17, IL-10, RANTES, the IL-1ra/IL-1 ratio, eotaxin, IL-1, IFN-, IL- 1Ra, IL-2R, IL-13, IFN-, IL-12p70, IL-5, MIP-1, and IL-15. Entry of the 15 inflammatory mediators and ratio as independent predictors in a multiple linear regression model with Hb as the dependent variable demonstrated that IL-12p70 (standardized partial regression coefficient -weight 0.240, P 0.015) and IFN- ( -weight 0.293, P 0.001) positively predicted Hb levels (Table 3). Although not reaching statistical significance, IL-10 ( -weight 0.161, P 0.058) and IFN- ( -weight 0.175, P 0.067) also appeared to be important positive predictors of Hb levels. Conversely, IL-2R ( -weight 0.309, P 0.001), eotaxin ( -weight 0.266, P 0.009), and IL-13 ( -weight 0.290, P 0.004) inversely predicted Hb levels (Table 3). To determine the predictors of Hb among the subset of children with SMA, similar analyses that included only the SMA group (n 80) were performed. The LAR analysis identified the following 8 inflammatory mediators as the best predictors of Hb in the SMA group (listed in order of predictive strength): MIG, IL-5, IL-4, IL-1, IL-2R, IL-10, IL-12p70, and GM-CSF. Multiple linear regression analysis with the 8 inflammatory mediators as independent predictors and Hb as the dependent variable demonstrated that only IL-12p70 significantly predicted Hb levels ( -weight 0.288, P 0.017) in

4 VOL. 79, 2011 BIOMARKERS FOR MALARIAL ANEMIA SEVERITY 4677 TABLE 2. Inflammatory mediator levels and ratios in children presenting with acute malaria a Inflammatory mediator or ratio children with SMA (Table 3). Although none of the inflammatory mediators inversely predicted Hb levels at a P value of 0.050, IL-2R emerged as a marginally significant predictor ( -weight 0.201, P 0.084) (Table 3). DISCUSSION It is of great significance that biomarkers of malaria disease severity be identified to enable a better understanding of how inflammatory mediators influence disease pathogenesis and clinical outcomes. In the past several years, inflammatory mediators have been investigated as potential biomarkers of cerebral malaria and mortality (2, 16, 20), as well as of malaria outcomes during pregnancy (21, 51). Recently, using an in vitro model of erythropoiesis, we demonstrated that soluble mediators of inflammation associated with childhood SMA can suppress erythropoiesis in the novel model by decreasing erythroid proliferation and maturation (3). In the current study, we took an expanded approach by measuring a large panel of inflammatory mediators (n 25) to identify biomarkers that are predictive of malarial anemia in an area of P. falciparum transmission endemicity in which the primary clinical manifestation of falciparum malaria is SMA (6). Results presented here are consistent with previous studies showing that low levels of IL-12p70 (22, 26, 41), IL-10 (23), IFN- (26), and IFN- (26) are associated with more severe Median level (pg/ml) (IQR) for indicated group UM (n 31) Non-SMA (n 37) SMA (n 80) P value b Cytokine or ratio IL (323.6) (309.3) (277.7) IL-1Ra 2,300.7 (2,396.8) 2,297.1 (2,082.3) 1,450.3 (2,021.0) IL (104.5) 24.1 (66.1) 31.4 (61.4) IL-2R 1,039.0 (1,577.5) 2,072.0 (1,085.5)** 2,129.0 (2,737.7)** <0.001 IL (23.1) 1.7 (8.0)* 4.9 (15.6) IL (4.5) 1.4 (3.0) 1.6 (2.6) IL (175.4) 68.7 (189.2) 97.9 (140.5)* IL (47.0) 8.5 (45.2) 1.3 (33.6) IL (27.3) 11.9 (18.6) 15.3 (22.8) IL (660.8) (745.5)* (570.5) <0.001 IL-12p (279.9) (301.3) (221.3) IL (53.9) 29.6 (32.9) 29.5 (48.6) IL (87.4) 22.4 (60.8) 26.9 (38.3) IL (24.8) 10.1 (19.3) 4.7 (11.3) TNF (39.3) 22.0 (51.1) 31.3 (49.2) IFN (122.8) 12.3 (51.5) 8.4 (53.5) IFN (59.2) 8.0 (25.7) 4.2 (14.1) IL-1Ra/IL (45.4) 15.0 (52.1) 11.8 (46.3) IL-2R/IL (96.7) 71.1 (879.1)* 70.0 (174.3)** Growth factor or chemokine GM-CSF 84.4 (362.5) 18.3 (137.5) 39.7 (164.5) MIP (137.2) (87.0) (105.0) MIP (688.6) (399.6) (362.3) IP (694.3) (1,155.4)* (509.2) MIG (155.0) (216.5) (157.5) Eotaxin 40.3 (22.5) 35.0 (32.8) 42.8 (27.8) RANTES 18,176 (100,486) 13,952 (37,060) 17,270 (144,999) MCP (235.9) (235.8) (199.1) a n, number of children with that type of malaria., P 0.050,, P b Differences were determined using Kruskal-Wallis tests, and where significant differences were observed, pairwise comparisons with the UM group were performed using Mann-Whitney U tests. Boldface indicates a P value of disease in children with malaria. The data presented here also support previous investigations in which increased levels of IL-1Ra (17, 20), IL-2R (18), IL-6 (17, 27), and the IL-2R/IL-2 ratio (43) were correlated with more severe malaria in pediatric cohorts. However, levels of a number of inflammatory mediators previously associated with disease severity, such as IL-1 (19), IL-8 (27), TNF- (26, 27), MIP-1, MIP-1 (34), IP-10 (16), the IL-1Ra/IL-1 ratio (20), and RANTES (19, 34, 49), did not differ significantly across the three clinical groups in the current study. This apparent discrepancy may plausibly be explained by the fact that, in the current study, all children had acute malaria infection, while in previous studies, comparisons were made that included children who (i) were without malaria infections (i.e., aparasitemic or healthy controls) (16, 27, 34, 49), (ii) were in the convalescent period of disease (26), and/or (iii) had more previous exposure and acquired immunity by virtue of being older (19, 27). Differences observed here and previously are also likely related to differing malaria disease manifestations: the current study included only those children with anemia as a clinical outcome, whereas previous investigations included a mixed phenotype of disease characterized by cerebral malaria, hyperparasitemia, and SMA. Furthermore, unlike previous investigations, the current study excluded children with copathogens, since additional pathogens in children with malaria affect the inflammatory milieu. Although a number of recent studies have acknowledged the

5 4678 ONG ECHA ET AL. INFECT. IMMUN. TABLE 3. Predictors of malarial anemia severity a Predictor by group of children and by block b -wt Semipartial r 2 Block statistics All children Block 1 R , P Age Gender Sickle cell trait G6PD deficiency Block 2 R , P IL IL RANTES IL-Ra/IL Eotaxin IL IFN IL-1Ra IL-2R IL IFN IL-12p IL MIP IL Children with SMA Block 1 R , P Age Gender Sickle-cell trait G6PD deficiency Block 2 R , P MIG IL IL IL IL-2R IL IL-12p GM-CSF a The full model was significant at F(19, 128) 3.454, P 0.001, R 0.582, and R , when all children (n 148) were considered, and at F(12, 67) 2.839, P 0.003, R 0.581, and R , for children with SMA (n 80). -Weights and semipartial r 2 values with P values of are marked in bold. b Block 1 includes the -weights and semipartial r 2 values of the covariates on their own, without the inflammatory mediator levels, among all children and among children with SMA, while block 2 involves the -weights and semipartial r 2 values of the inflammatory mediators among all children and among children with SMA, controlling for the confounding effects of the covariates. importance of inflammatory mediators as potential biomarkers of malaria disease severity (2, 16, 20, 21, 51), there continues to be a lack of clear insight into the complexity of the immune response. The complexity is underscored by the fact that production of most inflammatory mediators is typically intercorrelated (20), with the directionality of the immune responses and/or the accumulation of the effector cells within the deeper tissues being more informative than the absolute magnitude of cytokine levels (14). To address immunological complexities, there has been a move toward the use of mathematical/statistical modeling as a tool to unravel these complex relationships (48). Examples of successful modeling include biomarkers for the prediction of biochemical recurrence following prostatectomy (46) and characteristic inflammatory responses during hemorrhagic shock (47). In the current study, we modeled biomarkers for the prediction of anemia (Hb levels) using LAR and multiple linear regression analysis. LAR was selected for the modeling since it is a versatile computational application for high-dimensional data sets that can select a parsimonious set of predictors, which can then be used for prediction of a response variable (in our case, Hb) (12). In our total-sample analysis, LAR identified 15 inflammatory mediators (Table 3), 60% of which had levels that differed significantly or were of borderline significance across the groups (Table 2). However, although IL-4, IL-6, and the IL-2R/IL-2 ratio differed significantly across the groups, these were not identified as top priorities in the LAR analysis. This can be explained by the fact that the LAR analysis took into account the correlations among the predictor variables; such predictor colinearity cannot be disentangled in conventional between-group univariate comparisons. After identifying the parsimonious set of predictors with LAR analysis, a multiple linear regression analysis identified IL-12p70 and IFN- as significant positive predictors of Hb. Consistent with the analysis that included all children in the data set, analyses that included only children with SMA identified IL-12p70 as a significant predictor of Hb. Identification of IL-12p70 and IFN- as significant positive predictors of Hb using these novel approaches supports previous observations showing that enhanced production of IL-12p70 and IFN- are associated with reduced malarial anemia severity (22, 26, 37, 41). In addition, the emergence of IL-12p70 and IFN- in the human modeling presented here supports investigations in murine models demonstrating that IL-12 promotes erythropoiesis by augmenting the formation of erythroid burst-forming units (BFU-E) and CFU (CFU-E) (31, 32). It is important to note that SMA was defined in the current study as Hb levels of 6.0 g/dl, based on a previous study in the same region that defined the distribution of Hb levels in the population by performing 14,000 longitudinal Hb measurements in children less than 48 months of age (29). Given that the sample size was reduced from 80 to 39 using a cutoff criterion of Hb levels of 5.0 g/dl to define SMA, an appropriate subject-to-predictor ratio for the modeling translates into the ability to examine only half of the number of predictors. Although we postulate that the same predictors will emerge when using the cutoff criterion of Hb levels of 5.0 g/dl, additional studies with an appropriate number of P. falciparum-infected children with Hb levels of 5.0 g/dl are required to confirm this prediction. The observation that IL-13 and eotaxin emerged in the modeling as significant negative predictors of Hb levels is intriguing. IL-13 is a powerful anti-inflammatory cytokine that regulates inflammation and immune responses (30) and is primarily associated with allergic responses and helminthic infections (44, 52). Eotaxin was recently reported to prevent hematopoietic cell differentiation by blocking their signaling through expression of suppressors of cytokine (SOCs) (45). Furthermore, in the context of HIV-1/malaria coinfection, we recently observed that HIV-1-exposed and HIV-1-positive children with worsening anemia (40) had elevated levels of eotaxin relative to HIV-1-negative children (G. C. Davenport, J. B. Hittner, T. Were, J. M. Ong echa, and D. J. Perkins, submitted for publication). In addition, eotaxin is a strong chemoattractant for

6 VOL. 79, 2011 BIOMARKERS FOR MALARIAL ANEMIA SEVERITY 4679 eosinophils (42), which are also associated with allergic reactions (44). However, eosinophil responses have been reported during malaria infections (25) and are important for producing functional IL-13 (44). Since eosinophil responses are associated with hematological recovery following malarial treatment (8) and Hb levels typically decrease following successful parasite clearance with antimalarial drugs (7), it is tempting to postulate that the IL-13/eotaxin pathway may negatively regulate Hb levels during a malaria infection through eosinophilic responses. Kurtzhals et al. (25) observed that during acute infection, eosinophils were sequestered in deep tissues, while recent studies showed that the production of high levels of IL-13 in malaria-infected children was associated with hepatomegaly (52). Eosinophils are known to produce granule proteins (e.g., eosinophil cationic protein [ECP]) whose levels are correlated with TNF- and IL-2R during malarial infections (25). Findings presented here showing that soluble IL-2R levels are significant negative predictors of Hb levels are consistent with previous studies showing that elevated IL-2R is associated with enhanced malaria disease severity (18). The potential effect of the IL-13/eotaxin pathway on erythropoiesis and the influence of IL-2R in regulating this process are largely unexplored. As such, further investigation of this pathway in children with malaria, coupled with the novel in vitro model of erythropoiesis recently developed (3), may offer important insight into this largely unexplored pathway. Based on findings presented here and placed into the context of previous studies, we propose a model in which IL-12 and IFN- are two of the primary cytokines responsible for promoting successful erythropoiesis in children with malaria (31, 32), while high levels of IL-2R may serve to dampen excessive type 1 immunity (18). The model further proposes that eotaxin may recruit eosinophils to the deeper tissues (including bone marrow), where they and other cell types may produce IL-13 to dampen the inflammatory responses (30), but in the process, direct effects of protein granules (or other local toxic mediators) may contribute to the suppression of erythropoiesis. This model is consistent with studies showing elevated levels of eotaxin in bone marrow (9) and suppressed maturation of bone marrow dendritic cells in individuals with chronic graft-versus-host disease (4). Moreover, the suppressive effect of eotaxin on hematopoietic cell differentiation (45) may also explain the presence of numerous eosinophil precursors trapped in the bone marrow of African children with malaria (1). In summary, by using statistical modeling in conjunction with high-throughput assays that concomitantly measured 25 inflammatory mediators in a comprehensively phenotyped cohort of children with malaria, we identified IL-12p70 and IFN- as significant positive predictors of Hb levels and IL-2R, eotaxin, and IL-13 as significant inverse predictors of Hb levels. Although some of the molecules examined here have previously shown associations with malaria disease outcomes, concomitant investigation of a large panel of potential biomarkers (n 25) offered the unique advantage of identifying novel pathways, such as the IL-13/eotaxin pathway, which may be an important inflammatory network in malaria that requires further exploration. As the technological capacity continues to expand and the magnitude of potential biomarkers increases rapidly, we will continue to be faced with the practical realities associated with the number of study participants that can be recruited and clinically managed, particularly in resource-poor settings. The use of mathematical tools, such as LAR analysis, may offer some ability to deal with the common and growing problems associated with a high number of predictors in a limited participant base. ACKNOWLEDGMENTS We are grateful to the parents, guardians, and children from the Siaya District community in western Kenya for their participation in the study. We also thank all the University of New Mexico-Kenya Medical Research Institute (KEMRI) staff and the Siaya District Hospital staff for their support during this study. We thank the director of the Kenya Medical Research Institute for approving the article for publication. This work was supported by the National Institutes of Health (grants R01 AI and D43 TW to D.J.P.) and the Fogarty International Center (grant R01 TW to J.M.O.). The content is the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. There is no conflict of interest reported by any of the authors of the paper due to commercial or other affiliations. REFERENCES 1. Abdalla, S. H Peripheral blood and bone marrow leucocytes in Gambian children with malaria: numerical changes and evaluation of phagocytosis. Ann. Trop. Paediatr. 8: Armah, H. B., et al Cerebrospinal fluid and serum biomarkers of cerebral malaria mortality in Ghanaian children. Malar. J. 6: Awandare, G. A., et al Mechanisms of erythropoiesis inhibition by malarial pigment and malaria-induced proinflammatory mediators in an in vitro model. Am. J. Hematol. 86: Banovic, T., et al Graft-versus-host disease prevents the maturation of plasmacytoid dendritic cells. 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