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Carcinogenesis Advance Access originally published online on October 20, 2006
Carcinogenesis 2007 28(3):704-712; doi:10.1093/carcin/bgl200
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Published by Oxford University Press 2006
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Polymorphisms in immune function genes and risk of non-Hodgkin lymphoma: findings from the New South Wales non-Hodgkin Lymphoma Study

Mark P. Purdue1,*, Qing Lan1, Anne Kricker2, Andrew E. Grulich3, Claire M. Vajdic3, Jennifer Turner4, Denise Whitby5, Stephen Chanock1,6, Nathaniel Rothman1 and Bruce K. Armstrong2

1 Division of Cancer Epidemiology and Genetics, National Cancer Institute Rockville, MD, USA
2 The University of Sydney, Sydney Australia
3 National Centre for HIV Epidemiology and Clinical Research, Sydney Australia
4 St Vincent's Hospital, Sydney Australia
5 Viral Epidemiology Section, AVP SAIC-Frederick, NCI-Frederick, Frederick, MD, USA
6 Core Genotyping Facility, National Cancer Institute Gaithersburg, MD, USA

*To whom correspondence should be addressed at: Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, 6120 Executive Boulevard, EPS 8121, MSC 7240, Rockville, MD 20892-7240, USA. Tel: +1 301 451 5036; Fax: +1 301 402 1819; Email: purduem{at}mail.nih.gov


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 References
 
Recent findings suggest that genetic polymorphisms in TNF and IL10 are associated with an increased risk of non-Hodgkin lymphoma (NHL), particularly for diffuse large B-cell lymphoma (DLBCL). To further investigate the contribution of common genetic variation in key cytokine and innate immunity genes to the etiology of NHL, we genotyped participants in a case–control study of NHL conducted in Australia (545 cases, 498 controls). We investigated 36 single nucleotide polymorphisms in IL10, TNF and 21 other immune function genes. We observed an elevated risk of DLBCL with the IL10 –3575T>A polymorphism [TA genotype: odds ratio (OR) = 1.32, 95% confidence interval (CI) = 0.86–2.02; AA, OR = 1.84, 95% CI = 1.10–3.08; trend test, P = 0.02]. Our most noteworthy TNF finding was an association between –857C>T and a decreased risk of NHL (CT or TT, OR = 0.59, 95% CI = 0.42–0.84, P = 0.003) and particularly follicular lymphoma (OR = 0.40, 95% CI = 0.23–0.68, P = 0.0009). Additionally, TNF –863C>A was associated with an elevated risk of DLBCL (CA, OR = 1.45, 95% CI = 0.95–2.21; AA, OR = 2.06, 95% CI = 0.88–4.83; trend test, P = 0.02). Our findings offer further evidence that variation in the IL10 and TNF loci influences NHL risk. Additional studies are needed to clarify the genetic and biologic basis for these relationships.

Abbreviations: DLBCL, diffuse large B-cell lymphoma; FDR, false-discovery rate; FPRP, false-positive report probability; HWE, Hardy–Weinberg equilibrium; NHL, non-Hodgkin lymphoma.


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 References
 
Cytokines are secreted proteins that play a critical role in regulating the immune system; they control lymphoid cell development and differentiation, and regulate the balance between the T-helper, Th1 and Th2, immune responses. Given these biologic properties, there is reason to postulate that cytokine activity might influence the pathogenesis of non-Hodgkin lymphoma (NHL). That baseline measures of cytokines and immunoglobulins are associated with subsequent risk of developing NHL in prospective studies of AIDS patients (1–4) and predict prognosis and disease progression in NHL patients (5–13) support this hypothesis.

Evidence that common polymorphisms in cytokine genes influence their expression (14–16) raises the possibility that such polymorphisms might influence susceptibility to NHL. IL10 and TNF are good candidate genes for the study of lymphomagenesis because they code for immunoregulatory cytokines that are critical mediators of inflammation, apoptosis and Th1/Th2 balance, and function as autocrine growth factors in lymphoid tumors (17–19). Moreover, studies of IL10 and TNF knockout mice have shown that each cytokine affects B-cell lymphomagenesis directly or indirectly (20–22).

A recent pooled analysis of eight case–control studies of NHL participating in the InterLymph Consortium showed that carriage of the TNF –308G>A variant was associated with an increased risk of NHL generally and diffuse large B-cell lymphoma (DLBCL) in particular (23). This association was highly statistically significant, consistently observed across InterLymph studies, and robust upon application of the false-discovery rate (FDR) and false-positive report probability (FPRP) methods. An increased risk of DLBCL associated with the IL10 –3575 polymorphism was another, but less robust, finding of this pooled analysis. These findings justify further investigation of the LTA-TNF and IL10 loci in NHL, including replication of the association between DLBCL and IL10 –3575.

To this end, we genotyped these loci in participants in a population-based case–control study of NHL conducted in New South Wales, Australia. In addition, we investigated whether putatively functional polymorphisms in other immune function genes were associated with NHL risk.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 References
 
Cases
A detailed description of the design and methods of this case–control study has previously been published (24). The study was approved by the human research ethics committee at each participating institution. Briefly, patients notified to the New South Wales (NSW) Central Cancer Registry with newly diagnosed NHL between 1 January 2000 and 31 August 2001 who were 20–74 years of age and resident in NSW or the Australian Capital Territory (ACT) were potentially eligible to be cases. Pathology reports for consenting cases were reviewed by an anatomical pathologist with a particular interest in hematopathology (J.T.) to assess confidence in the diagnosis of NHL and to assign, where possible, a cell phenotype and WHO (ICD-03) code (25).

Altogether, 1,217 apparently eligible cases (694 males, 523 females) were ascertained for the study; 197 of them were subsequently found to be ineligible because of prior immunosuppression or immune deficiency (n = 28), poor English (n = 73), illness (n = 74) or disability preventing interview (n = 22). A further 178 were excluded from the possibility of interview because they had died (n = 144) or could not be contacted (n = 34). Of the remaining 842 who were approached for interview, 125 refused and 717 were interviewed. Twenty-three of those interviewed were excluded after pathology report (n = 13) or slide review (n = 10) because of low confidence in the diagnosis of NHL (26), leaving 694 cases (85%) for analysis.

Controls
Controls were randomly selected from the NSW and ACT electoral rolls to match approximately the expected distributions of cases with respect to age, sex and residence (NSW or ACT). The intended case–control ratio was 1:1. A total of 1687 apparently eligible controls were randomly selected for the study; 145 of them were subsequently found to be ineligible because of poor English (n = 74), illness (n = 59) or disability preventing interview (n = 12). A further 406 were excluded from the possibility of interview because they had died (n = 5) or could not be contacted (n = 401). Of the 1136 who were approached for interview, 442 refused and 694 (61%) were interviewed.

Data collection
All eligible individuals were mailed an introductory letter and an information leaflet outlining the requirements of participation and then telephoned to obtain their verbal consent. Subjects completed a self-administered postal questionnaire and a computer-assisted telephone interview that collected information on a variety of putative risk factors including infectious and allergic conditions, vaccinations, lifetime sun exposure, occupational exposures, and use of pesticides and hair dyes. At the conclusion of the interview, subjects were asked if they would be willing to receive some written information about blood testing. Those willing were sent a letter asking for consent to obtain a blood specimen, information sheet and consent form. Upon receipt of signed consent, each consenting subject was sent a blood collection pack and asked to take it with them to a nearby pathology service blood collection point or to their doctor. A total of 19 ml of blood was collected, including a 9 ml EDTA whole blood tube and two 5 ml serum tubes. Genomic DNA was extracted from the buffy coats of blood samples using Qiagen QIAamp® DNA Blood Midi Kits by laboratory staff at SAIC Frederick.

Five hundred and ninety seven cases and 525 controls provided blood. After exclusions due to inadequate DNA quantity (6 cases, 3 controls) or to other issues related to sample handling and DNA quality (7 cases, 4 controls), DNA samples from 584 cases (85% of participants, 69% of eligible contactable individuals) and 518 controls (75%, 46%) were available for genotyping.

Genotyping and quality control
Genotype analysis was done at the National Cancer Institute Core Genotyping Facility (http://cgf.nci.nih.gov). All TaqMan® assays (Applied Biosystems Inc., Foster City, CA, USA) were optimized on the ABI 7900 HT detection system with 100% concordance with sequence analysis of 102 individuals listed on the SNP500Cancer website (http://snp500cancer.nci.nih.gov) (27).

We selected 36 SNPs in 23 immune function genes for analysis (Table I). These SNPs were selected either because they had been assessed in the InterLymph pooled analysis of cytokine polymorphisms (23), or because they had a minor allele frequency (MAF) ≥ 0.05 and one of the following: laboratory evidence of functional relevance, or previous evidence of association with human disease. Duplicate samples from 95 study subjects were interspersed throughout each batch for all genotyping assays. The concordance rates for QC samples were 98–100% for all assays. One SNP was found to deviate slightly from Hardy–Weinberg equilibrium (HWE) among controls of European ancestry (TNF –863C>A, P = 0.03); quality control data were rechecked and the accuracy of this assay was confirmed.


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  		Table I Genes and single nucleotide polymorphisms (SNPs) evaluated

 
Statistical analysis
The analysis was restricted to individuals of European ancestry (545 cases, 498 controls; 94% of study subjects) in order to be comparable to the InterLymph analysis. All statistical analyses were conducted using SAS Version 8.2 (SAS Institute, Cary, NC, USA). All statistical tests were two-sided with an alpha level of 0.05. The chi-square test was used to identify departures from HWE among controls. To estimate the relative risk of NHL in relation to SNP genotype, odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using unconditional logistic regression, adjusting for sex, age (<40, 40–49, 50–59, 60–69 and 70+) and European ancestry (British or Irish, or Western or Northern, Southern, Eastern or mixed European origin). Data for homozygotes and heterozygotes were combined if there were fewer than five homozygotes in cases or controls. For each SNP, tests for trend were conducted by assigning the ordinal values 1, 2 and 3 to homozgyous wild-type, heterozygous and homozygous variant genotypes, respectively, and by modeling these scores as a continuous variable. In addition to conducting analyses of overall NHL, we calculated subtype-specific ORs for the two most prevalent histologic subtypes of NHL: follicular lymphoma (FL; n = 205) and DLBCL (n = 173). To assess differences in ORs between these subtypes, we made case–case comparisons for each variant (analyzed assuming the additive model) using unconditional logistic regression.

Haplotype analyses were done for all genes that had multiple polymorphisms assessed. Haplotypes were estimated using the estimation-maximization algorithm in SAS Genetics (SAS Institute, Cary, NC, USA). An unconditional logistic regression model was used to estimate the effect of individual haplotypes by fitting an additive model, adjusting for sex, age and European ancestry. The overall (global) difference in haplotype frequencies between cases and controls was assessed using the likelihood ratio test.

To explore how the findings from this study would have contributed to the InterLymph pooled analysis, we did a meta-analysis of the risk estimates from individual studies using the random effects model of DerSimonian and Laird (28). Two sets of summary ORs and P-values were calculated for each InterLymph polymorphism; the first set excluded findings from the NSW study, while the second set included these findings.

We assessed the robustness of our findings for individual SNP loci by applying the FDR (29) and the FPRP (30) methods to the P-values from genotype comparisons made assuming the additive model. For the FDR method, the 36 comparisons with all NHL were assessed as one set, and the 72 subtype-specific comparisons were assessed as a separate set. FPRP estimates were calculated across a range of prior probabilities (0.00001–0.1) and for different ORs assuming a non-null association (1.2, 1.4 and 1.6). We considered findings with an FPRP ≤ 0.20 to be noteworthy.


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 References
 
The distributions of cases and controls were similar with respect to sex and age but there was a somewhat higher prevalence of British or Irish ancestry among cases than controls (Table II). Most cases were B-cell lymphomas, predominantly FL and DLBCL (Table II).


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  		Table II Characteristics of genotyped study participants (n = 1043)

 
The findings for IL10 variants are summarized in Table III. While risk of all NHL was not significantly associated with any of the four IL10 polymorphisms assessed, DLBCL cases were appreciably more likely than controls to carry the –3575A and –1082G alleles (Ptrend = 0.02 and 0.06, respectively), as was observed in the InterLymph pooled analysis. The test for difference in the trend ORs between FL and DLBCL was statistically significant for –3575 (P = 0.04). The –853 and –592 variants were not associated with DLBCL.


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  		Table III Associations between IL10 variants and risk of overall NHL, FL and DLBCL; analyses by genotype and haplotypea

 
The A-G-C-C haplotype formed by the alleles at the four IL10 loci studied (–3575, –1082, –853, –592) was more common among DLBCL cases than controls (P = 0.01 versus all other haplotypes combined). We also did a specific analysis of the haplotypes formed by the alleles at loci –3575 and –1082 to try to separate the effects of the polymorphisms at these loci (linkage disequilibrium statistics: D' = 0.97, r2 = 0.65). Only the A-G (double variant) haplotype was associated with a significantly increased risk of DLBCL (OR = 1.32, 95% CI = 1.00–1.73) relative to T-A (double wild-type). The OR for the T-G haplotype, which includes only the –1082 variant allele, was 0.88 (95% CI = 0.53–1.46); the A-A haplotype was rare (0.004 of all haplotypes).

The findings for variants in LTA and TNF, which lie adjacent to one another on 6q21, are given in Table IV. One SNP, TNF –857C>T, was significantly associated with all NHL. The –857T allele was less common among cases than among controls (P = 0.003 for test of CT or TT versus CC), particularly for FL (P = 0.0009). Increased risks of DLBCL were observed for carriage of LTA –91C and TNF –863A (test for trend: P = 0.05 and 0.02, respectively). To explore the sensitivity of the TNF –863 finding to the observed departure from HWE among controls, we calculated crude ORs for DLBCL across genotypes using the control genotype frequencies expected under HWE. The association remained and was, if anything, slightly stronger after adjustment (OR = 1.24, 2.97 for AC and AA, respectively, versus CC). The TNF –308 and LTA 252 polymorphisms were not significantly associated with NHL or either subtype.


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  		Table IV Associations between variants in LTA and TNF and risk of overall NHL, FL and DLBCL; analyses by genotype and haplotypea

 
We analyzed haplotypes for the six LTA-TNF SNPs (LTA –91, LTA 252, TNF –863, TNF –857, TNF –308). The haplotype frequencies were statistically significantly different between cases and controls for all NHL and FL (P = 0.04, 0.03, respectively); for DLBCL the P-value was 0.11. For each outcome, the A-A-C-T-G-G haplotype (containing TNF –857T) was associated with significantly decreased risks of all NHL and FL (P = 0.01 and 0.002, respectively) relative to A-A-C-C-G-G, the all wild-type haplotype. An increased risk of DLBCL was observed for the C-A-A-C-G-G haplotype, containing LTA –91C and TNF –863A (P = 0.009).

Polymorphisms in other immune function genes were also found to be associated with NHL or one of its major subtypes (Table V). The IFNGR2 Ex7-128T and FCGR2A Ex4-120A alleles were associated with reduced and increased risks of DLBCL, respectively (P = 0.04, 0.06, respectively, for test of heterozygotes and homozygous variant type combined), although there was no dose–response relationship with allele copy number for either polymorphism. The IL4 –1098G allele was also associated with an increased risk of DLBCL (P = 0.05). Cases were less likely than controls to carry the TGFB1 Ex1-327C allele (P = 0.008 for test of CT or CC vs. TT), although there was no dose-response relationship with allele copy number (Ptrend = 0.11). When analyzed by subtype, this association was slightly stronger for FL than for DLBCL, but this difference was not statistically significant.


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  		Table V Associations between SNPs in IFNGR2, FCGR2A, IL4, TGFB1 and risk of all NHL, FL and DLBCLa

 
We also observed a non-significant (P = 0.09), 2-fold increased risk of DLBCL among individuals heterozygous for the CARD15 Ex11-35->C mutation, although only a small number of subjects carried the mutation (online supplement).

Applying the FDR and FPRP methods to assess the robustness of our findings showed that associations of TNF –857T with all NHL and with FL met FDR criteria of 13 and 10%, respectively, and were noteworthy given a prior probability of 0.1 or greater.

The findings for the immune function gene polymorphisms listed in Table I that were not significantly associated with all NHL or either major subtype are given in an online supplement (online supplement).

We conducted a meta-analysis to see how our findings contributed to those of the pooled analysis of InterLymph SNPs (23). Using a random effects model, the additive-model summary OR for DLBCL in relation to IL10 –3575A remained virtually unchanged upon inclusion of the NSW result (InterLymph studies: OR = 1.16; InterLymph + NSW: OR = 1.18); however, the P-value for this association decreased by nearly an order of magnitude (0.004–0.0005). When we applied the FPRP method to these findings, we observed that the inclusion of the NSW estimate resulted in a more robust association (InterLymph studies: noteworthy at prior probability ≥ 0.1; InterLymph + NSW, noteworthy at prior probability ≥ 0.01). Upon addition of the NSW finding for TNF –308A, there was no meaningful change in the DLBCL summary OR for this variant (1.29 to 1.26), the corresponding P-value (0.00007 to 0.0001) or the FPRP estimates of robustness. The pooled estimates for the other InterLymph SNPs also did not change appreciably with inclusion of the NSW findings (data not shown).


   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
References
 
Our findings provide additional evidence to that provided by the InterLymph pooled analysis (23) for influences of genetic variation in IL10 and LTA-TNF on susceptibility to NHL. In addition, we observed significant associations with NHL or one of its major subtypes with polymorphisms in IFNGR2, FCGR2A, IL4 and TGFB1.

In our study, the IL10 variants –3575A and –1082G were associated with an increased risk of DLBCL. Additional haplotype analyses of these polymorphisms demonstrated that the elevated risk of DLBCL was restricted to the AG haplotype (containing both risk alleles) rather than the TG haplotype (containing only the –1082 risk allele), suggesting that –3575A is more important than –1082G in influencing the risk of lymphoma. These findings confirm those of the InterLymph pooled analysis. Our replication of the IL10 –3575 findings from the pooled analysis is important, since the InterLymph result for this SNP was less robust than that for TNF –308. The results of our meta-analysis suggest that the inclusion of data from our study in the InterLymph analysis would have resulted in a meaningfully more robust IL10 –3575 finding. The IL10 –3575A allele has been reported to be associated with lower IL-10 production than the T allele (31). The pathogenetic significance of IL-10 is unclear. It has been hypothesized that lower expression of IL-10, a potent downregulator of TNF-{alpha} and other macrophage proinflammatory cytokines, may increase lymphoma risk by less efficiently suppressing proinflammatory cytokine production (23). However, others have postulated that IL-10, as a B-cell stimulatory cytokine, may promote lymphomagenesis (32). In support of this alternative hypothesis is evidence that a putatively high IL-10-expressing genotype (–592 CC) is associated with increased risk of AIDS-associated NHL (32). These seemingly conflicting findings may point to IL-10 dysregulation in general as being important as a contributing factor to NHL development.

The cytokines TNF-{alpha} and LT-{alpha}, encoded by TNF and LTA, respectively, are thought to influence lymphomagenesis through up-regulation of proinflammatory and anti-apoptotic signals, possibly via the nuclear transcription factor (NF)-{kappa}B pathway (23). For this locus, we found a significantly reduced risk of all NHL and of FL associated with the TNF –857T allele. TNF –857T was also reported to be associated with a decreased risk of FL in a population-based case–control study in England (33), and was inversely associated with gastric mucosa-associated lymphoid tissue (MALT) lymphoma in a clinic-based study in Taiwan (34). Other studies of NHL, however, have either failed to find an association with this SNP (35,36), or observed a positive association between it and gastric lymphoma (37). While the –857T allele has been associated with decreased ex vivo levels of TNF-alpha in whole blood upon LPS stimulation (38), other studies investigating the functional effects of TNF –857 by other methods have yielded different findings, and no clear consensus has emerged (39–42). It is, however, consistently associated with a decreased risk of Crohn's disease and ulcerative colitis (38,43), thus suggesting that it does have functional effects.

At the same locus, we also observed positive associations of the TNF –863A allele, which has been reported to be associated with increased TNF expression in vitro (41,42, 44,45), and the LTA –91C allele, a nearby variant, with DLBCL. TNF –863A was also associated with an increased risk of NHL, and DLBCL in particular, in the case–control study from England (33), though no association between it and MALT lymphoma was observed in the study from Taiwan (34). Two other studies that assessed LTA –91 observed no association with this variant (34,36).

We found only weak evidence of a relationship between TNF –308 and DLBCL risk, although the small excess of the G allele in DLBCL cases was in the same direction as the robust association observed in the InterLymph pooled analysis (23). The inclusion of our –308 finding in a meta-analysis with those from the InterLymph pooled analysis did not meaningfully alter the summary OR and corresponding P-value for DLBCL. Interestingly, the TNF findings from our study population of predominantly British ancestry are very similar to those from the study of NHL from England (33). In each study, associations with NHL were observed for the –863 and –857 polymorphisms, with similar findings by subtype, but not for –308.

We also observed associations with NHL for polymorphisms in IFNGR2, FCGR2A, IL4 and TGFB1. Similar findings for some of these SNPs have been reported in other studies. We found that the FCgamma 2A receptor gene (FCGR2A) Ex4-120A allele was associated with an increased risk of DLBCL. This allele, which creates a codon for the amino acid arginine instead of histidine, has been reported to be associated with an excess risk of NHL in another case–control study (35), and a more rapid disease progression in a follow-up study of NHL patients (46). Our observation of an increased risk of DLBCL accompanying carriage of IL4 –1098G is similar to the positive association between this allele and NHL risk reported in a previous study (36). The TGFB1 Ex1-3271C allele, which was associated with reduced NHL risk in our study, has been consistently reported to be associated with increased expression (47–49) of TGF-ß, a potent inhibitor of cell proliferation and inducer of apoptosis for many cell types, including B lymphocytes (50).

Strengths of this study include its population-based design, relatively large sample size, high participation rate among cases and extensive assessment of immune function gene polymorphisms. The study also has some limitations. The participation rate among controls was comparatively low, with 61% of contactable controls having participated and 46% genotyped. However, selection bias is an improbable explanation for our findings, since willingness to participate and provide blood is unlikely to be related to cytokine genotype differences (51). Given that we assessed many SNPs, examined relationships both overall and by major subtype, and had a comparatively small sample size for subtype-specific analyses, there is the possibility of false-negative and false-positive (30) findings. Indeed, after applying the FDR and FPRP methods to our findings, only the associations with TNF –857 appeared to be reasonably robust. However, our findings for IL10 and LTA/TNF are consistent with the published literature in suggesting that these loci influence susceptibility to NHL. As for the other immune function genes, it is important for these findings to be replicated in other studies if meaningful inferences as to their causal relevance are to be drawn.

Our findings add important additional evidence in support of a relationship between variants in the IL10 and LTA/TNF loci and susceptibility to NHL, and suggest other immune function genes worthy of further investigation. Additional work is needed to clarify the genetic and biologic basis for these relationships. In particular, there is a need for investigations that incorporate dense haplotype-tagging SNP selection to provide good coverage of variation across the entire span of these genes.


   Acknowledgments
 
We gratefully acknowledge the individuals who participated in the research, the clinicians who gave permission for us to approach their patients, and staff at the NSW Central Cancer Registry and the Hunter Valley Research Foundation. Special thanks to Melisa Litchfield, Maria Agaliotis and Chris Goumas for data collection and data entry and to Jackie Turner for telephone follow-up. We thank Wendell Miley for co-ordinating DNA extraction and sample aliquoting and the members of the VES who performed DNA extractions. We also thank Robert Welch and Sunita Yadavalli at the NCI Core Genotyping Facility for their work in the specimen handling and laboratory analysis of genotyping data, and Sonja Berndt at the NCI Division of Cancer Epidemiology and Genetics for conducting the meta-analysis. The NSWNHL study was funded by the National Health and Medical Research Council of Australia, The Cancer Council NSW, and The University of Sydney Medical Foundation. The genotyping project was funded by the Intramural Research Program at the NIH (National Cancer Institute).

Conflict of Interest Statement. None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 References
 

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