Dectin-1 and DC-SIGN Polymorphisms Associated with Invasive Pulmonary Aspergillosis Infection

The recognition of pathogen-derived structures by C-type lectins and the chemotactic activity mediated by the CCL2/CCR2 axis are critical steps in determining the host immune response to fungi. The present study was designed to investigate whether the presence of single nucleotide polymorphisms (SNPs) within DC-SIGN, Dectin-1, Dectin-2, CCL2 and CCR2 genes influence the risk of developing Invasive Pulmonary Aspergillosis (IPA). Twenty-seven SNPs were selected using a hybrid functional/tagging approach and genotyped in 182 haematological patients, fifty-seven of them diagnosed with proven or probable IPA according to the 2008 EORTC/MSG criteria. Association analysis revealed that carriers of the Dectin-1 rs3901533 T/T and Dectin-1 rs7309123 G/G genotypes and DC-SIGN rs4804800 G, DC-SIGN rs11465384 T, DC-SIGN 7248637 A and DC-SIGN 7252229 C alleles had a significantly increased risk of IPA infection (OR = 5.59 95%CI 1.37–22.77; OR = 4.91 95%CI 1.52–15.89; OR = 2.75 95%CI 1.27–5.95; OR = 2.70 95%CI 1.24–5.90; OR = 2.39 95%CI 1.09–5.22 and OR = 2.05 95%CI 1.00–4.22, respectively). There was also a significantly increased frequency of galactomannan positivity among patients carrying the Dectin-1 rs3901533_T allele and Dectin-1 rs7309123_G/G genotype. In addition, healthy individuals with this latter genotype showed a significantly decreased level of Dectin-1 mRNA expression compared to C-allele carriers, suggesting a role of the Dectin-1 rs7309123 polymorphism in determining the levels of Dectin-1 and, consequently, the level of susceptibility to IPA infection. SNP-SNP interaction (epistasis) analysis revealed significant interactions models including SNPs in Dectin-1, Dectin-2, CCL2 and CCR2 genes, with synergistic genetic effects. Although these results need to be further validated in larger cohorts, they suggest that Dectin-1, DC-SIGN, Dectin-2, CCL2 and CCR2 genetic variants influence the risk of IPA infection and might be useful in developing a risk-adapted prophylaxis.


Introduction
Invasive Pulmonary Aspergillosis (IPA) is a life-threatening infection caused mainly by Aspergillus fumigatus, an opportunistic fungal pathogen that frequently colonizes respiratory tracts and rapidly spreads to blood vessels and tissues [1]. The incidence of IPA infection has increased in the last years due to the use of immunosuppressive and immunomodulatory drugs and is still causing significant morbidity and mortality worldwide, especially in immunosuppressed and hematopoietic stem cell transplantation (HSCT) patients [2].
Early recognition of A. fumigatus by myeloid leukocytes is a crucial for down-stream immune response and conidia clearance and, therefore, in the development and progression of IPA infection [3]. Myeloid leukocytes are activated by patternrecognition receptors (PRRs), which directly recognize fungal cell wall structures and pathogen-associated molecular patterns (PAMPs) [4]. Among the PRRs expressed in neutrophils, pulmonary macrophages and dendritic cells, C-type lectin family members such as DC-SIGN (Dendritic Cell-Specific Intercellular adhesion molecule-3-Grabbing Non-integrin), Dectin-1 (Dendritic cell-associated C-type lectin-1) and Dectin-2 (Dendritic cellassociated C-type lectin-2) seem to be important in the effectiveness of innate immune response against A. fumigatus [5,6]. Recent studies have reported that the C-type lectins mediate A. Fumigatus recognition, capture and internalization [7] and that their binding to fungal cell wall carbohydrates is highly specific and selective [8]. DC-SIGN and Dectin-1 recognize b-(1-3)-glucans and galactomannans (GM) in the cell wall of A. fumigatus [7,9] while Dectin-2 interacts with a-mannans [10]. However, numerous studies have shown that C-type lectins are not only involved in the recognition of fungal pathogens but also in the induction of antifungal Th1 and Th17 immune responses [5,11].

Study population and clinical diagnosis of IPA infection
All participants enrolled were Caucasian and recruited in the University Hospital Virgen de las Nieves (Granada, Spain) or in the University Hospital of Salamanca (Salamanca, Spain). All determinations and genetic analyses in hematological patients were performed with fully informed written consent, and anonymity of the data was guaranteed. The study protocol was approved by the Ethical Review Committee of Virgen de las Nieves University Hospital, Granada, Spain. The population included 182 hematological patients recruited between January 2004 and January 2011. All hematological patients in this study received a prolonged chemotherapy treatment or underwent HSCT and were therefore considered susceptible to develop IPA infection. Demographic information and clinical data were obtained by detailed review of hospital records. Data were gathered on: site of infection; host factor criteria (severe neutropenia for .10 days, persistent fever for .96 h refractory to appropriate broad-spectrum antibacterial treatment, signs and symptoms indicating graft-versus-host disease [GVHD], corticoid therapy [.0.3 mg/kg per day], and invasive fungal infection during a previous episode of neutropenia), microbiological criteria (positive result for Aspergillus antigen in $2 consecutive blood samples when considering an index of 0.5 or in only 1 sample when the index was higher than 0.8), and clinical criteria of lower respiratory tract infection [major criteria: any of the following new infiltrates on computed tomography (CT) imaging: halo sign, aircrescent sign, or cavity within area of consolidation; minor criteria: cough, thoracic pain, hemoptysis, pathologic pulmonary sound, and radiological evidence suggestive of invasive infection]. Laboratory data were also recorded. Proven and probable IPA was diagnosed based on the updated criteria (2008) reported by the European Organization for Research and Treatment of Cancer/Invasive Fungal Infections Cooperative Group (EORTC/ IFICG) [31].

Quantification of serum galactomannan antigen
Serum GM detection has been shown to be a useful test for the early diagnosis and follow-up of IPA and is now included in IPA diagnosis criteria [31]. In the present study, serum GM antigen was determined twice weekly during the hospital stay and at each outpatient visit until the end of their immunosuppressant or chemotherapeutic treatment. Serum GM concentrations were determined by Platelia Aspergillus ELISA kit (Bio-Rad, Marnes-la-Coquette, France) according to the manufacturer's instructions. This commercial kit has proven to offer good sensitivity to detect GM [32], and GM concentration was found to correlate with the fungal tissue burden [33,34]. A test sample was classified as positive when the optical density ratio was $0.5 in two consecutive positive samples or .0.8 in a unique serum sample. A careful review of concomitant treatments (piperacillin-tazobactam or amoxicillin-clavulonic acid) in each patient was necessary to detect possible false-positive GM determinations. Likewise, tests were performed on the same day to avoid sample contamination and to ensure accuracy of results.

SNP selection and genotyping
Twenty-seven tagging/functional SNPs within DC-SIGN, Dectin-1, Dectin-2, CCL2 and CCR2 were selected to genotype the entire panel of individuals ( Table 1). The aim of the SNP tagging was to identify a set of SNPs that efficiently tags all the known SNPs while the functional approach was used to determine the net impact of potentially functional variants within DC-SIGN, Dectin-1, Dectin-2, CCL2 and CCR2 genes on IPA risk. Tagging SNPs were selected using Haploview Tagger program (http://www.broad.mit.edu/ mpg/haploview/; http://www.broad.mit.edu/mpg/tagger/) and a pairwise tagging with a minimum r2 of 0.8. In this selection we forced the inclusion of the DC-SIGN rs4804803 , CCL2 rs1024610 and CCL2 rs1024611 polymorphisms as their functionality has been suggested [35][36][37]. Genomic DNA was extracted from peripheral blood mononuclear cells (PBMCs) Qiagen Mini Kit (Qiagen, Valencia, CA, USA). Genotyping of DC-SIGN, Dectin-1, Dectin-2, CCL2 and CCR2 polymorphisms was carried out using KASPar assays (KBiosciences, Hoddesdon, Hertfordshire, UK) in a 384well plate format (Applied Biosystems, Foster City, CA, USA) where hematological patient samples were randomly distributed. KASPar reactions were performed using KASPar assay mix (containing probes) and KASPar kit containing 26 Reaction Mix and MgCl2 (50 mM). PCR conditions were: denaturation at 94uC for 15 min, 10 cycles of denaturation at 94uC for 10 sec, annealing at 57uC for 5 sec and elongation at 72uC for 10 sec and 20 cycles of denaturation at 94uC for 10 sec, annealing at 57uC for 20 sec and elongation at 72uC for 40 sec. Recycling conditions were 94uC for 10 sec, annealing and elongation at 60uC for 60 sec. PCR products were analyzed with the ABI Prism 7900HT detection system using the SDS 2.4 software (Applied Biosystems). For internal quality control, about 5% of samples were randomly selected and included as duplicate. Concordance between the original and the duplicate samples for the 27 SNPs analyzed was $99.5%. Call rates for all SNPs were $97.8% with the exception of the Dectin-1 rs11053599 SNP with a call rate of 94.5%.

Statistical analysis
The Hardy-Weinberg Equilibrium (HWE) tests were performed in the control group (non-IPA patients) by a standard observedexpected chi-square (x 2 ) test at each polymorphic site (http://ihg2. helmholtz-muenchen.de/cgi-bin/hw/hwa1.pl). Unconditional logistic regression was used to assess the main effects of the genetic polymorphisms on IPA risk using co-dominant, dominant and recessive inheritance models. For each SNP, the more common allele in the control group was assigned as the reference category. All analyses were adjusted for age, gender, hematological malignancy and established risk factors for IPA infection (HSCT, neutropenia, GVHD and corticoid therapy use) and were conducted using the statistical software SSPS (version 14.0, SPSS Inc., Chicago, USA). All tests were considered to be statistically significant with a p value of ,0.05. Adjustment for multiple testing was carried out following a conservative threshold for statistical significance, based on a revised version of the Bonferroni method: we calculated for each gene the ''number of effective independent variables'' (M eff ) by use of the SNP Spectral Decomposition approach (http://gump.qimr. edu.au/general/daleN/SNPSpDsuperlite/) [38]. We obtained a study-wise M eff value by adding up the gene M eff 's. SNPtool (http://www.dkfz.de/de/molgen_epidemiology/tools/ SNPtool.html) [39] and the Haploview v4.2 software were used for LD blocks reconstruction and haplotype association statistics. Block structures were determined according to the method of Gabriel et al. [40].

Functional prediction of associated SNPs
We used the Web-based tool FastSNP [41] available at http:// fastsnp.ibms.sinica.edu.tw for predicting the functional significance of the SNPs associated with IPA infection. FastSNP utilizes information from another online program PolyPhen (http://www. bork.embl-heidelberg.de/PolyPhen/) and from four different web resources (TFSearch, ESEfinder, Rescue-ESE and FAS-ESS) to determine whether SNPs are located at exonic splicing regulatory sites, cause a non-conservative amino acid change or whether they alter the transcription factor-binding site of a gene (for instance, acting as intronic enhancer). The score was given by this tool on the basis of levels of risk with a ranking of 0 (no effect), 1 (very low), 2 (low), 3 (medium), 4 (high), or 5 (very high).

RNA extraction, reverse transcription, and qPCR
Whole blood samples from 21 healthy donors were collected into PAXGENE RNA tubes and stored at 280uC until use. Total RNAs were extracted using a PAXGENE Blood RNA Isolation Kit (PreAnalytiX) and reverse transcribed to cDNA using QuantiTect Reverse Transcription Kit (catalog number: 205311; Qiagen). Real-time quantitative PCR was carried out using an ABI PRISMH 7500 HT Sequence Detection System (Applied Biosystems) according to manufacturer's instructions. Briefly, 2 ml of the cDNA were loaded in a PCR reaction containing 12.5 ml of 26 QuantiTect SYBR Green PCR Master Mix with an appropriate concentration of MgCl 2 , 2.5 ml of primers (Hs_CLE-C7A_1_SG QuantiTect Primer Assay, catalog number: QT00024059; Geneglobe, Qiagen) and 8 ml of RNase-free water. PCR cycling conditions were as follows: 95uC for 15 minutes, followed by 40 cycles of denaturation at 95uC for 15 seconds combined with annealing at 60uC for 30 seconds and extension at 72uC for 30 seconds. All samples were run in duplicate. Relative quantification of Dectin-1 mRNA expression was calculated with the 2 2DDCt method. We obtained the fold changes in gene expression normalized to an internal control gene (GAPDH, Hs_GAPDH_2_SG QuantiTect Primer Assay, Catalog number: QT01192646; Qiagen) and relative to one calibrator (First-

SNP-SNP interaction analysis
We also analyzed high-order interactions between SNPs using the multifactor dimensionality reduction (MDR) constructive induction algorithm. A detailed explanation on the MDR method has been described elsewhere [42,43]. SNPs in LD (cut-off of r 2 ,0.8) were excluded from the MDR analysis. Cross-validation and permutation testing were used to identify the best models. All possible two-, three-and four-way SNP interactions were tested using 100-fold cross-validation and the exhaustive search. The model with the highest testing balanced accuracy (TA) and cross validation consistency (CVC) was selected as ''best model''. Statistical significance was evaluated using a 1.000-fold permutation test to compare observed testing balanced accuracies with those expected under the null hypothesis of no association (using the MDR permutation testing module 0.4.9 alpha). MDR results were considered statistically significant at the 0.05 level. Finally, interactions were visualized by constructing an interaction dendrogram according to the method described by Moore et al [43]. MDR software and MDR permutation testing module are open-source and freely available from http://www.epistasis.org.

Results
Population characteristics are described in Table 2. Compared to non-IPA, IPA cases were more likely to have cough and pathologic pulmonary sound (p,0.001 and 0.011, respectively) and presented more often pathological chest radiographies and CT scans (p,0.001). Established risk factors for IPA infection such as HSCT, neutropenia, GVHD and corticoid therapy use were homogenously distributed between IPA and non-IPA patient groups.
Fifty-seven patients were diagnosed with proven or probable IPA infection according to the revised EORTC/MSG criteria (2008). The association of risk of IPA infection with the individual 27 SNPs in the C-type lectin and chemokine genes is shown in the Table S1. All analyzed polymorphisms fulfilled Hardy-Weinberg expectations for the control group (non-IPA patients). Several polymorphisms were found to be associated with IPA infection ( Table 3) Table 3 and Table S1). After correction for multiple testing using SNPSpD (number of independent marker loci, 21; p = 0.05/21 = 0.002), none of the SNPs retained significance although Dectin-1 rs7309123 showed significance when the carrier status was analyzed (CC+CG vs. GG, P = 0.001; Table 3).
In order to assess the degree to which the selected SNPs and the positivity of GM correlated, we also performed lineal regression analysis. In the whole population, 3784 assays were performed in duplicate and 531 were considered as positive (14.03%). We found a significantly higher percentage of positive GM among patients carrying the Dectin-1 rs3901533_T allele and among those patients bearing the Dectin-1 rs7309123_G/G genotype suggesting a role of these polymorphisms in determining a defective recognition and clearance of Aspergillus conidia (Figure 1). No correlation was observed for the polymorphisms within DC-SIGN that were associated with the infection.
We subsequently assessed whether SNPs associated with IPA infection showed capacity to change putative transcription factor binding sites using FastSNP. The predictive functional analysis suggested an intronic enhancer function for the Dectin-1 rs7309123 SNP due to its location in transcription factor Cdxa (caudal type homeo-box transcription factor 1) binding site (GAAAGAC; score 1-2). These data suggest a central role of the rs7309123 in the susceptibility to IPA infection. None of the remaining SNPs associated with IPA infection was predicted to affect transcription factor binding sites or splicing or to introduce a damaging amino acid change.
To explore the potential consequences of Dectin-1 rs7309123 SNP, Dectin-1 mRNA expression was measured in 21 healthy donors and was correlated with genotypes. Our results showed that subjects harbouring GG genotype showed a significantly decreased level of Dectin-1 mRNA expression compared to C-allele carriers (p,0.001; Figure 2). These results further supported our hypothesis suggesting that Dectin-1 rs7309123_G allele may disrupt binding sites for potential transcription factors. The MDR analysis of the SNPs tested revealed statistically significant interactions. Two SNPs (rs1024611 and rs4264222) were excluded from the MDR analysis as they were in LD with other SNPs using a cut-off value of r 2 ,0.80 in our sample set. The best interaction models selected by the TuRF filter algorithm along with its testing accuracy and cross-validation consistency are shown in Table 4. The overall best model with the highest crossvalidation consistency (CVC) consisted of a model that included the CCL2 rs4586 , Dectin-1 rs3901533 , CCR2 rs3918358 and Dectin-2 rs7134303 SNPs. This model had a significant testing accuracy of 0.7735 (permutation p,0.001) and a cross-validation consistency of 100/ 100. Of note is that two SNPs showing genetic interaction in this model were not significantly associated with an increased risk of IPA infection in the univariate analysis (CCR2 rs3918358 and Dectin-2 rs7134303 ). The best two-locus model consisted of the Dectin-1 rs3901533 and DC-SIGN rs4804800 SNPs, two variants that showed also association in the single-locus analysis. This model had a testing accuracy of 0.6409 and a cross-validation consistency of 76/100. This model was not any more significant after 1.000-fold permutation testing. However, the entropy based information gain calculated for this pair of SNPs indicated strong synergy, which may be interpreted as the two SNPs acting together to increase the risk of IPA infection. The best three-locus model included the CCL2 rs4586 , Dectin-1 rs3901533 and Dectin-2 rs7134303 SNPs. In this model, testing accuracy raised to 0.7085 (permutation p = 0.025) whereas the cross-validation consistency was of 68/100. Figure 3 illustrates an interaction dendogram that summarizes the estimates of interactions.
We found that polymorphisms in Dectin-1 (rs3901533 and rs7309123) and DC-SIGN (rs4804800, rs11465384, rs7248637 and rs7252229) were associated with an increased risk to develop IPA infection, which points towards their critical involvement in the pathogenesis of this invasive fungal infection. The highest risk of IPA infection was found for carriers of the Dectin-1 rs3901533_T/T and Dectin-1 rs7309123_G/G genotypes and the DC-SIGN rs4804800_G allele. Patients carrying these genotypes/alleles had from 2 to 6 times increased risk of IPA infection. Additionally, patients carrying the DC-SIGN rs11465384_T , DC-SIGN 7248637_A and DC-SIGN rs7252229_C alleles showed a 2-fold increased risk in comparison with patients harboring the wild-type allele. Although it was not statistically significant, we also found that the DC-SIGN rs2287886 SNP may be associated with a reduced risk of IPA infection. Interestingly, this latter result was in agreement with our  previously reported findings using the former EORTC/MSG classification criteria, 2005 [60]. The apparent effect of these SNPs on IPA susceptibility persisted even after adjustment for age, gender, hematological malignancy and several known risk factors (HSCT, neutropenia, GVHD and corticoid therapy use), indicating that Dectin-1 and DC-SIGN variants contribute independently to the risk of infection.
Another interesting finding of this study was the significantly greater positive GM percentage of patients carrying the Dectin-1 rs3901533_T allele than those with the wild-type allele. Additionally, patients harboring the G/G genotype for the Dectin-1 rs7903123 SNP showed an increased percentage of positive GM compared to those carrying the C allele (C/C+C/G). No differences were found when positive GM determinations were correlated with DC-SIGN polymorphisms. These data along with the remarkable degree of association of Dectin-1 and DC-SIGN variants with risk of IPA infection provides a compelling evidence for a critical role for these PRRs in immune response to IPA infection. In this regard, numerous studies have shown that Dectin-1 and DC-SIGN are not only involved in the recognition of fungal pathogens but also in the induction of anti-fungal Th1 and Th17 immune responses [5,11].
Mezger et al. also demonstrated that Dectin-1 is involved in the induction of several pro-inflamatory cytokines, chemokines and immune receptors [18] while Werner et al. showed that Dectin-1 is also regulating Th17-mediated immune response in the lungs [61]. Furthermore, Dennehy and Brown suggested a role of Dectin-1 mediating its own signaling, as well as synergizing with TLRs to trigger NFkB-mediated immune response against fungal pathogens [62].
Although it is now well recognized that SNPs in genes modulating immune response are likely to be determinants of host susceptibility to fungal infections, so far, little is known regarding the biological significance of these variants. In order to shed light into the potential functionality of Dectin-1 (rs3901533 and rs7309123) and DC-SIGN (rs4804800, rs11465384, rs7248637, rs7252229 and rs2287886) variants, we investigated whether they were involved in disruption of a binding site for critical transcription factors that might influence transcription level of these genes. Our predictive analysis showed that the carriage of the C allele for the Dectin-1 rs7309123 SNP creates a putative binding site for Cdxa, a relatively unknown transcription factor, which might be involved in the control of Dectin-1 gene expression. To assess whether the Dectin-1 rs7309123 polymorphism might be associated with a decreased expression of Dectin-1, we correlated Dectin-1 mRNA expression levels with Dectin-1 rs7309123 genotypes. Interestingly, we observed that individuals harbouring the GG genotype showed a relatively lower expression than those carrying the C allele (CC+GC). These results further supported our hypothesis suggesting that Dectin-1 rs7309123 SNP may have an effect on the Dectin-1-mediated recognition of Aspergillus conidia and subsequent immune responses. However, this predicted change in transcription activity is only suggestive at this stage and will need further validation using in vitro functional assays.
Several lines of evidence point to the relevance of epistatic effects in the etiology of complex diseases but, up to now, no studies have been carried out to analyze the presence of SNP-SNP interactions in IPA infection. For this reason, we decide to assess interactions among genetic polymorphisms within DC-SIGN, Dectin-1, Dectin-2, CCL2 and CCR2, genes and the risk of IPA infection. The MDR approach used in this study was able to determine two multilocus combinations associated with high risk to develop IPA infection. Of the interactions identified, MDR indicated that the type of interaction in the two significant models was synergistic. These results support the hypothesis that multiple SNP-SNP interactions may play a role in determining the risk of IPA infection. This hypothesis is biologically plausible since the immune system would warrant prevention of fungal infection even when some genetic variants were present.
Recent population-based studies have even led to the identification of several SNPs involved in the early recognition of Aspergillus and associated them with an increased risk for invasive fungal infection. It has previously been suggested that SNPs within C-type lectin genes are associated with fungal infections. Platinga et al. (2009) and Cunha et al. (2010) suggested that patients carrying the Y238X (rs16910526) polymorphism in the Dectin-1 gene were more likely to be colonized with Aspergillus and Candida species [19,63], compared with those harboring the wild-type allele. However, these results were not replicated in a very recent study [24]. In our study, such findings were neither evidenced even when HSCT and non-HSCT patients were analyzed separately (data not shown). This puzzling finding suggests that, although intronic polymorphisms within Dectin-1 and DC-SIGN are indeed themselves a strong indication that these genes play an important role in the susceptibility to IPA infection, we cannot rule out the Figure 3. Interaction dendrogram generated by the MDR software. The interaction dendrogram was used to confirm, visualize, and interpret the interaction model. The MDR analysis was performed by using the open-source MDR software package. The colors used depict the degree of synergy, ranging from red (highest information gain) to blue (highest information redundancy). Note that the interaction between Dectin-1 (rs3901533) and DC-SIGN (rs4804800) SNPs showed the highest degree of synergy (gain of information). doi:10.1371/journal.pone.0032273.g003 possibility that these SNPs are part of a bigger haplotype containing important other genetic variants in the neighboring genes. In any case, because all these population-based studies have been conducted using relatively small cohorts, additional studies in larger set of patients are needed to definitely establish the role of these variants in the susceptibility to invasive fungal infection.
In summary, this study provides evidence of association between Dectin-1 and DC-SIGN polymorphisms and the risk of IPA infection. By the inclusion of functional prediction analyses, the correlation of genotypes with positive GM determinations and Dectin-1 mRNA expression levels, the study strongly supported the role of Dectin-1 gene variants in determining susceptibility to IPA infection. Epistatic analyses also suggested the presence of a gene-gene interaction involving Dectin-1 with CCL2 and CCR2 variants to determine IPA infection. Despite all these evidences, additional studies using larger cohorts will be necessary to confirm the effect of these polymorphisms on the susceptibility to IPA infection.

Supporting Information
Table S1 Associations of polymorphisms involved in the phagocyte-immune related response against Aspergil-lus. 1 Models adjusted for age, gender, hematological malignancy, HSCT, neutropenia (defined as absolute neutrophil count ,500 cells/mm3 for a period of more than 10 days), GVHD and corticoid therapy use (.0.3 mg/Kg/day). { Assuming a recessive model of inheritance. Abbreviations: OR, odds ratio; CI, confidence interval. Differences in samples numbers are due to failures in genotyping. (DOC)