² # CHANDAB Ghinaj ¹ , ² # , PETIT Roula ¹ Ajrouche
email: rola_ajrouche@hotmail.com

Ghinaj Chandab

Arnaud Petit

Marion Strullu

Brigitte Nelken

Geneviève Plat

Gérard Michel

Carine Domenech

Jacqueline Clavel

Audrey Bonaventure

Strullu Arnaud³

Marion

Nelken Brigitte

Plat Geneviève

Michel Gérard

Domenech Carine

Clavel Jacqueline¹

Bonaventure Audrey¹

Allergies, genetic polymorphisms of Th2 interleukins, and childhood acute lymphoblastic leukemia: The ESTELLE study

Keywords: Childhood leukaemia, lymphoblastic leukaemia, allergy, cytokines, gene-environment interaction, gene-gene interaction, aetiology, case-control studies, epidemiology, genetics

come

Introduction

Accounting for approximately one third of all childhood neoplasms in high-income countries, childhood acute leukaemia (CL) is the most common malignancy diagnosed in childhood (0-14 years), with acute lymphoblastic leukaemia (ALL) representing about 80% of childhood leukaemia [START_REF] Bonaventure | Worldwide comparison of survival from childhood leukaemia for 1995-2009, by subtype, age, and sex (CONCORD-2): a population-based study of individual data for 89 828 children from 198 registries in 53 countries[END_REF] . Some risk factors have been clearly identified, such as exposure to high-level ionizing radiation [START_REF] Wakeford | The risk of childhood leukaemia following exposure to ionising radiation-a review[END_REF] or certain chemotherapeutic agents, Down's syndrome [START_REF] Botto | Cancer Risk in Children and Adolescents with Birth Defects: A Population-Based Cohort Study[END_REF] and a few rare genetic disorders [START_REF] Giacomazzi | Pediatric cancer and Li-Fraumeni/Li-Fraumeni-like syndromes: a review for the pediatrician[END_REF][START_REF] Alter | Fanconi anemia and the development of leukemia[END_REF][START_REF] Stiller | Epidemiology and genetics of childhood cancer[END_REF][START_REF] Zimmerman | A Catalog of Genetic Syndromes in Childhood Cancer: Catalog of Genetic Syndromes in Childhood Cancer[END_REF] . In the current context of uncertainty on the aetiology of ALL, the immune system increasingly appears to play a significant role in leukaemogenesis for lymphoid precursors [START_REF] Bonaventure | Worldwide comparison of survival from childhood leukaemia for 1995-2009, by subtype, age, and sex (CONCORD-2): a population-based study of individual data for 89 828 children from 198 registries in 53 countries[END_REF] . It is thought that an abnormal immune response due to lack of infections during early childhood may lead to the development of CL, particularly to ALL [START_REF] Greaves | Infection, immune responses and the aetiology of childhood leukaemia[END_REF] . This hypothesis meets the "hygiene hypothesis" proposed by Strachan as an explanation of the rising incidence of allergies in the Western population, which has also been related to lack of early immune stimulation [START_REF] Strachan | Hay fever, hygiene, and household size[END_REF] . While one would therefore expect a positive association between allergy history and ALL, the majority of epidemiological studies, often questionnaire-based, tended to show that children with CL had less allergies than children without CL [START_REF] Wen | Allergic disorders and the risk of childhood acute lymphoblastic leukemia (United States)[END_REF][START_REF] Schüz | Atopic disease and childhood acute lymphoblastic leukemia: Atopy and Childhood Leukemia[END_REF][START_REF] Silva | Infectious diseases in the first year of life, perinatal characteristics and childhood acute leukaemia[END_REF][START_REF] Rosenbaum | Allergy and infectious disease histories and the risk of childhood acute lymphoblastic leukaemia: Allergy, infectious disease and childhood ALL[END_REF] . Several studies assessed the association between allergies and CL based on objective data, with contrasting findings. An inverse association was observed in a study based on medical record [START_REF] Hughes | Allergy and risk of childhood leukaemia: Results from the UKCCS[END_REF] and a study based on immunoglobulin-E levels [START_REF] Lariou | Allergy and risk of acute lymphoblastic leukemia among children: A nationwide case control study in Greece[END_REF] , but not in an American study on medical records [START_REF] Spector | Medically recorded allergies and the risk of childhood acute lymphoblastic leukaemia[END_REF] , nor in a Taiwanese study using medico-administrative data [START_REF] Chang | Allergy and Risk of Childhood Acute Lymphoblastic Leukemia: A Population-based and Record-based Study[END_REF] . In 2011, lower levels of interleukin 10 (IL10) at birth were reported in ALL cases than in controls, suggesting an abnormal immune function at birth in ALL cases [START_REF] Chang | Profound Deficit of IL10 at Birth in Children Who Develop Childhood Acute Lymphoblastic Leukemia[END_REF] , and findings have suggested also that two IL10 polymorphisms were associated to ALL in Taiwan [START_REF] Lo | Significant Association of Interleukin-10 Polymorphisms with Childhood Leukemia Susceptibility in Taiwan[END_REF] . A metaanalysis reported this overall inverse association pattern, while highlighting the lack of consistency if a latency period was applied between the diagnosis of allergies and CL [START_REF] Linabery | The Association Between Atopy and Childhood/Adolescent Leukemia: A Meta-Analysis[END_REF] .

In our previous study, we have reported a negative association between a history of asthma or eczema and ALL that appeared to be modified by genetic polymorphisms of IL13 and IL10 Th2 cytokines [START_REF] Bonaventure | Genetic polymorphisms of Th2 interleukins, history of asthma or eczema and childhood acute lymphoid leukaemia: Findings from the ESCALE study (SFCE)[END_REF] but this remains to be confirmed with further studies on any allergy. Therefore, this study aimed to investigate the association between the risk of childhood ALL and a medical history of allergy, accounting for genetic polymorphisms of cytokines of the Th2 pathway (IL4, IL10, IL13 and IL4R), which could to modify this association.

Methods

The ESTELLE study is a French national population-based case-control study conducted in 2010-2011, designed to assess the role of several environmental and genetic factors in the aetiology of childhood cancers. The design of the ESTELLE study has been described [START_REF] Ajrouche | Maternal reproductive history, fertility treatments and folic acid supplementation in the risk of childhood acute leukemia: the ESTELLE study[END_REF][START_REF] Ajrouche | Childhood acute lymphoblastic leukaemia and indicators of early immune stimulation: the Estelle study (SFCE)[END_REF] . Briefly, eligible children were aged less than 15 years and residing in mainland France. They were not eligible if they had been adopted (5 leukaemia cases), or if they hadn't a living French-speaker biological mother without a serious psychiatric disorder (47 cases), or if the child was in palliative care or had died (8 cases). Cases were children diagnosed with leukaemia between January 2010 and December 2011, detected and enrolled by the investigators of the National Registry of Childhood Cancers (RNCE). Controls were initially identified from a randomly-generated telephone numbers (listed and unlisted). They were children free from cancer randomly selected from the French general population over the same period, using a quota sampling method (frequency matching), based on distributions of age and sex for all childhood cancers combined expected from the national childhood registry. The quotas also ensured that the control group had the same distribution as the general population regarding the number of children aged 0-14 years living in the household, conditional on age. In total, 801 cases of leukaemia and 1,662 controls were eligible, of which 746 cases (93%), including with 635 ALL cases, and 1,421 controls (85%) participated in the ESTELLE study. Individuals with Down syndrome were excluded from these analyses (7 CL, including 6 ALL cases).

Maternal interviews were conducted over the phone using standardised questionnaires, by the same trained interviewers for cases and controls. The questionnaire elicited information on sociodemographic characteristics, childhood environment and lifestyle, medical history and childcare history. Before the interview, mothers were asked to have the child health record booklet on hand, so they could get back to the records if needed (94% for controls and 82% of ALL cases). Specific items related to the child's history of allergy and specific symptoms diagnosed by a physician, such as asthma, allergic rhinitis or sinusitis, atopic dermatitis, eczema, food allergy, allergy to medications and desensitisation. For each allergic condition or symptom, mothers were asked to report the age at its diagnosis and whether any medication (corticosteroids, antihistamines or bronchodilators) had been prescribed. For food and drug allergies, information on the specific allergens was also collected. Biological specimens were also requested from each participant. Blood samples were taken from cases during care, and saliva samples collected at home using swab brushes for controls. Specimens were obtained from 602 ALL cases (95%) and 894 controls (63%). After DNA extraction, 499 cases and 777 controls were genotyped on a custom platform of 96 SNPs selected a priori, including our candidate polymorphisms in IL4, IL10, IL13 and IL4R. We excluded 6 ALL cases and 2 controls who did not pass quality controls (unsuccessful genotyping or discrepancy between reported and genotyped sex). Individual call-rates ranged from 61% to 100% in cases and 88% to 100% in controls, with the vast majority being above 90% (88% in cases and 96% in controls).

In order to limit the potential for population stratification bias, all genetic analyses were restricted to participants of European origin. Indeed, having both parents born in Europe, a proxy variable derived from the reported parents' country of birth, showed to be highly predictive of the Caucasian origin in our study (sensitivity 89%, specificity 79%). This left 411 ALL cases and 704 controls genotyped and from European origin available for analyses, hereafter referred to as "genotyped sample." The study protocols complied with the French regulations and the pertinent ethical approvals were obtained.

Our analyses focussed on a set of polymorphisms selected a priori [START_REF] Bonaventure | Genetic polymorphisms of Th2 interleukins, history of asthma or eczema and childhood acute lymphoid leukaemia: Findings from the ESCALE study (SFCE)[END_REF] because of their functional impact on the respective Th2 cytokines, and they had been reported to be associated with allergy, allergic symptoms or IgE level [START_REF] Yang | Association Between the Interleukin-4 Gene C-589T and C+33T Polymorphisms and Asthma Risk: A Meta-analysis[END_REF][START_REF] Liang | Interleukin 4 -590C/T (rs2243250) Polymorphism Is Associated With Increased Risk of Atopic Dermatitis: Meta-Analysis of Case-Control Studies[END_REF][START_REF] Li | Association between promoter polymorphisms of interleukin-4 gene and allergic rhinitis risk: a meta-analysis[END_REF][START_REF] Nie | Effects of Polymorphisms -1112C/T and +2044A/G in Interleukin-13 Gene on Asthma Risk: A Meta-Analysis[END_REF][START_REF] Chen | Single nucleotide polymorphisms of IL-13 and CD14 genes in allergic rhinitis: a meta-analysis[END_REF][START_REF] Zheng | Interleukin-10 Promoter 1082/-819/-592 Polymorphisms are Associated with Asthma Susceptibility in Asians and Atopic Asthma: A Meta-Analysis[END_REF][START_REF] Zhao | Association Between the IL-10-1082G/A , IL-10-592A/C , and IL-10-819G/A Polymorphisms and Atopic Dermatitis Susceptibility: A Meta-Analysis[END_REF][START_REF] Nie | Association between Interleukin-4 Receptor α Chain (IL4RA) I50V and Q551R Polymorphisms and Asthma Risk: An Update Meta-Analysis[END_REF] : rs20541 in IL13, the haplotype rs2070874-rs2243250 in IL4, the haplotype rs1800896-rs1800871-rs1800872 in IL10 and rs1801275 in IL4R.

There was no evidence for a deviation of the Hardy-Weinberg Equilibrium (HWE) for any of these candidate SNPs (p>0.05). The SNP call-rates were greater than 97%.

Each polymorphism was analysed independently, under a genotypic model and following a dominant model (carrying at least one variant allele vs. none). The haplotypes for IL4 and IL10 were derived from available genotypes since the corresponding polymorphisms (IL4-rs2070874 and rs2243250; IL10-rs1800871 and rs1800872) have been shown to be in linkage disequilibrium [START_REF] Flicek | Ensembl Project[END_REF] . For IL4, we focussed on the haplotype rs2070874-rs2243250 where CC is the reference and TT the double variant haplotype; for IL10, the rs1800896-rs1800871-rs1800872 haplotype CGG was the reference and TAT the triple variant haplotype of interest.

The association between allergy and ALL was analysed for each type of reported allergic symptom separately, and we also considered a category of 'any allergy', and of 'possibly IgE-mediated allergies' (asthma, allergic rhinitis/sinusitis, atopic dermatitis or food allergy) [START_REF] Zeiger | The development and prediction of atopy in high-risk children: Follow-up at age seven years in a prospective randomized study of combined maternal and infant food allergen avoidance[END_REF][START_REF] Niggemann | Predictors of positive food challenge outcome in non-IgEmediated reactions to food in children with atopic dermatitis[END_REF] . Analyses were performed in the whole ESTELLE study, and repeated in the genotyped sample of European ancestry.

Odds ratios and their 95% confidence intervals were estimated using unconditional logistic regression models. All analyses were adjusted for sex, age, and other factors, such as parental professional category, maternal education level, maternal age at child's birth, birth order, urban/rural status of the place of residence at birth, type of housing at birth and breastfeeding. The stability of the results was assessed after additional adjustments for contacts with dogs and farm animals in infancy and attendance to daycare nursery. Sensitivity analyses were also performed after applying a latency period, ignoring the allergies diagnosed in the same year as the ALL diagnosis (for cases) or recruitment (for controls). For asthma and allergic rhinitis, we also considered a specific category of children who had reportedly been prescribed antihistamines, corticoids or bronchodilators. Further analyses were carried out by ALL subtype. Interactions were assessed using likelihood ratio tests. ORs based on less than 5 exposed cases or controls are not shown. All tests were double sided; statistical significance was defined by p<0.05.

The SAS software package (version 9, Cary, NC, USA) was used for all analyses.

Results

Among the case group, there were 505 precursor-B cell leukaemia, 24 Burkitt ALL, 98 T-cell ALL and 2 unspecified ALL cases. The group of 411 genotyped cases included 333 precursor-B cell leukaemia and less common subtypes such as 64 T-cell ALL, 12 Burkitt and 2 other ALL. Table 1 shows the distribution of sociodemographic characteristics in cases and controls included in the whole ESTELLE study and in the subsample of genotyped children of European ancestry. In the complete sample, the distribution of educational levels and professional category were overall similar for the cases' and controls' parents. However, maternal educational level was associated with the case-control status in the subsample, with mothers tending to have higher educational levels in the control group. Maternal age at birth was also associated with the case-control status in the two samples, with mothers of cases tending to be younger. Cases were more likely than controls to be first-born children, and not to have been breastfed, in broadly similar proportions in the whole and restricted samples. The distribution of the parents' countries of birth was no different between cases and controls (not shown).

In the whole ESTELLE study, childhood ALL was not significantly associated with a history of allergy (any allergy, adjusted OR=0.91 [0.74-1.13]) (table 2). An inverse, not statistically significant, association was however observed with IgE-related allergies (OR=0.80 [0.63-1.03], p=0.09). No significant association was found with a history of asthma, atopic dermatitis, or eczema, but an inverse association was observed between ALL and a history of allergic rhinitis or sinusitis (OR=0.65 [0.42-0.98], p<0.05), which was also observed when restricting the definition of the exposition to children who reportedly took antihistamines or corticosteroids treatment. A borderline inverse association was also observed with food allergies (OR=0.62 [0.38-1.02], p=0.06). These associations were also observed in the genotyped subsample with the same order of magnitude, although the association with rhinitis/sinusitis no longer reached statistical significance.

When applying a latency period, similar associations were found between ALL and history of allergy but none were statistically significant (supplementary table 1). The inverse association with allergic rhinitis or sinusitis appeared more marked with B-cell precursor ALL than with T-cell ALL (supplementary table 2). These associations remained similar when excluding cases without a landline phone.

The associations between the candidate polymorphisms and ALL in the genotyped sample are presented in table 3. No significant association was observed between the genotypes of the candidate polymorphisms of the IL10, IL13, IL4 and IL4R genes and ALL, including the TT variant haplotype of IL4 (OR=0.83 [0.61-1.12], p>0.20) and the triple IL10 variant haplotype TAT (OR=1.27 [0.97-1.67], p=0.08). There was however a gene-gene interaction between IL4 and IL4R polymorphisms (pint=0.003), with IL4 variant haplotype being strongly associated with ALL in carriers of IL4R-rs1801275 variants (Interaction OR IOR=2.61 [1.39-4.91]) (Table 4).

Table 5 shows the findings of gene-environment interaction analyses between a reported history of allergy, the candidate polymorphisms and childhood ALL. We observed an inverse interaction between IL4R-rs1801275 genotype and a history of allergy (IOR=0.53 [0.30-0.96], pint=0.03), and more specifically with asthma (IOR=0.23 [0.08-0.71], pint=0.008) and eczema (IOR=0.47 [0.21-1.03], pint=0.06). The results also suggested that there may be an interaction between IL4 TT haplotype and any allergy (IOR=0.49 [0.25-0.93], pint=0.03), and between the TAT haplotype of IL10 and atopic dermatitis (IOR=2.33 [0.88-6.23], pint=0.09), but not with other allergic symptoms.

There was no evidence of an interaction between allergy history and IL13 polymorphism.

The associations were very similar after adjustment for attending a day-care nursery before 1 year and contact with dogs and farm animals before the age of 1 year. OR estimates were not changed after restricting genetic analyses to subjects with a call-rate of more than 90%.

Discussion

In this population-based national case-control study, there was no obvious association between ALL and allergies overall, but ALL was inversely associated with allergic rhinitis/sinusitis and food allergy. We also observed an interaction between variants of IL4 and IL4R, and an interaction between IL4R-rs1801275 and a history of several reported allergic symptoms, such as asthma or eczema. No interaction was observed with the candidate polymorphism IL13-rs20541.

In the ESTELLE study, the cases identification was based on the data collection system of the French RNCE, with a high participation rate (93%), thus ensuring a relative exhaustiveness of case recruitment. Only 1% of cases were ineligible for medical reasons (palliative care or death), making survival bias very unlikely to affect our results. The controls were sampled in the French general population with the same eligibility criteria as the cases. Due to the identification of controls through a list of randomly-generated landline numbers, a selection bias could have occurred because children living in households without landline number couldn't be recruited as controls, while cases with a mobile phone only (10% of the cases) were included. However, sensitivity analyses showed similar associations between allergy and ALL after excluding cases with no landline. In the control group, the acceptance of the biological sampling was related to age and socio-demographic factors such as the maternal educational level. Hence, all models were systematically adjusted for maternal educational level and the socioprofessional category of the parents. The genotyping of cases and controls was performed using the same 96-SNP bespoke platform, not allowing to run a principal component analysis to determine the Caucasian origin.

However, the restriction of analyses of genetic data to subjects born to European parents has limited a possible bias of population stratification.

The study was based on the data collected via a questionnaire that, although it was constructed to help accurate recall, relied on the memory of children's mothers, with a potential for recall bias.

In this study however, 94% of the control mothers and 82% of the case mothers had their child's health records on hand during the interview, as a support to help them recall medical events accurately. Moreover, restricting the definitions of allergy history to subjects receiving corresponding treatments and considering a latency showed associations of similar magnitude, therefore going against such a bias.

A systematic adjustment was considered on potential confounders previously shown to be associated with ALL in the ESTELLE study in particular on maternal education level, birth order, urbanization level of the commune of residence, and breastfeeding, in addition to factors related to the selection of the genotyped sample. Adjusted analyses for each of these factors alone, or for all of them combined, have given very similar estimates and did not highlight any confounding effect. We cannot however rule out the possibility of residual confounding.

The size of the ESTELLE study allowed sufficient statistical power (>80%) for analysing the association between ALL and allergy history, most of which had a frequency between 10-20%.

The power of gene-environment interaction analyses in genotyped subsample varied between 40% and 60% for an IOR of 2 between the interleukins polymorphisms (frequency ranging from 10% to 40%) and history of allergy (frequency ranging from 10% to 20%), which could explain some absence of significant interactions such those related to food allergy. Like other studies, the multiplicity of statistical tests performed increases the risk of first-type error and prompts cautious interpretation.

The present study found an inverse association between ALL and some reported symptoms of allergic history such as allergic rhinitis/sinusitis and food allergy, which is in line with previous findings from other interview-based studies showing that ALL cases were generally less prone to allergic symptoms than controls [START_REF] Wen | Allergic disorders and the risk of childhood acute lymphoblastic leukemia (United States)[END_REF][START_REF] Schüz | Atopic disease and childhood acute lymphoblastic leukemia: Atopy and Childhood Leukemia[END_REF][START_REF] Silva | Infectious diseases in the first year of life, perinatal characteristics and childhood acute leukaemia[END_REF][START_REF] Rosenbaum | Allergy and infectious disease histories and the risk of childhood acute lymphoblastic leukaemia: Allergy, infectious disease and childhood ALL[END_REF][START_REF] Lariou | Allergy and risk of acute lymphoblastic leukemia among children: A nationwide case control study in Greece[END_REF][START_REF] Rudant | Childhood Acute Leukemia, Early Common Infections, and Allergy: The ESCALE Study[END_REF][START_REF] Linabery | Immune-Related Conditions and Acute Leukemia in Children with Down Syndrome: A Children's Oncology Group Report[END_REF][START_REF] Wallace | Allergies and Childhood Acute Lymphoblastic Leukemia: A Case-Control Study and Meta-analysis[END_REF][START_REF] Nishi | A case-control study of non-T cell acute lymphoblastic leukaemia of children in Hokkaido, Japan[END_REF][START_REF] Magnani | Parental occupation and other environmental factors in the etiology of leukemias and non-Hodgkin's lymphomas in childhood: a case-control study[END_REF][START_REF] Petridou | The risk profile of childhood leukaemia in Greece: a nationwide case-control study[END_REF] , and in a UK study using medical-record data [START_REF] Hughes | Allergy and risk of childhood leukaemia: Results from the UKCCS[END_REF] .

However, other studies based on medical records or administrative data did not find this inverse association [START_REF] Hughes | Allergy and risk of childhood leukaemia: Results from the UKCCS[END_REF][START_REF] Lariou | Allergy and risk of acute lymphoblastic leukemia among children: A nationwide case control study in Greece[END_REF][START_REF] Spector | Medically recorded allergies and the risk of childhood acute lymphoblastic leukaemia[END_REF][START_REF] Chang | Allergy and Risk of Childhood Acute Lymphoblastic Leukemia: A Population-based and Record-based Study[END_REF][START_REF] Petridou | The risk profile of childhood leukaemia in Greece: a nationwide case-control study[END_REF] . Recall bias has been frequently discussed as a reason for the discordance of the results from previous studies, depending on the source of information (interview vs medical records). Interestingly, in the UK study from Hughes et al [START_REF] Hughes | Allergy and risk of childhood leukaemia: Results from the UKCCS[END_REF] , the ORs derived from medical-record data were higher than those resulting from interview data and the validity analysis showed a moderate agreement between interviews and records. When considering a latency period in ESTELLE study, our results showed an association of the same order of magnitude, whereas in their meta-analysis including four studies with a latency period between the onset of atopy and leukaemia, Linabery et al. had reported a nearly completely attenuated association between atopy/allergy and childhood ALL [START_REF] Linabery | Immune-Related Conditions and Acute Leukemia in Children with Down Syndrome: A Children's Oncology Group Report[END_REF] .

We did not here replicate the OR of 1.3 [0.9-1.8] (p=0.14) between the IL4 double-variant TT haplotype and childhood ALL that we had previously reported (ESCALE study, 2003-2004; between-study pint=0.04) [START_REF] Bonaventure | Genetic polymorphisms of Th2 interleukins, history of asthma or eczema and childhood acute lymphoid leukaemia: Findings from the ESCALE study (SFCE)[END_REF] . In the ESCALE study, no association was observed between ALL and IL10 TAT haplotype, which is related to a decrease in the synthesis of cytokines, while our present findings support a slight positive association; a pooled analysis of the two datasets produced an adjusted pooled OR of 1.18 [0.97-1.44] (between-study pinteraction =0.47). Interestingly, in the NCCLS, Chang et al. found that cases of childhood ALL had lower IL10 blood levels at birth than controls, and they reported a positive association between childhood ALL and three polymorphisms in IL10, which is in agreement with our findings [START_REF] Chang | Profound Deficit of IL10 at Birth in Children Who Develop Childhood Acute Lymphoblastic Leukemia[END_REF] .

In our previous study, also based on a population-based national case-control comparison), we had analysed gene-environment interaction between Th2 cytokines and allergic symptoms, with a focus on asthma and eczema [START_REF] Bonaventure | Genetic polymorphisms of Th2 interleukins, history of asthma or eczema and childhood acute lymphoid leukaemia: Findings from the ESCALE study (SFCE)[END_REF] . This study had highlighted an inverse interaction between the IL10 TAT haplotype and a history of asthma (IOR=0.3 [0.1-1.0]; pint=0.04) on the risk of ALL, and noted the presence of a possible interaction between the history of asthma or eczema and IL13-rs20541 (IOR=1.9 [0.9-3.8]; pint=0.07) [START_REF] Bonaventure | Genetic polymorphisms of Th2 interleukins, history of asthma or eczema and childhood acute lymphoid leukaemia: Findings from the ESCALE study (SFCE)[END_REF] , which our current analyses do not support. In the present we observed an interaction between IL4R-rs1801275 genotype and a history of eczema that was not significant in ESCALE; pooling the data from ESCALE and ESTELLE, we found an adjusted pooled IOR of 0.64 [0.37-1.10], pint=0.10 (between-study pint>0.50).

We here report a significant gene-gene interaction between a haplotype of IL4, related to increased IL4 synthesis, and a variant of IL4R, which increases the signal transduction. In ESCALE, we had also estimated a positive interaction(IOR 1.8 [0.9-3.6]) [START_REF] Bonaventure | Genetic polymorphisms of Th2 interleukins, history of asthma or eczema and childhood acute lymphoid leukaemia: Findings from the ESCALE study (SFCE)[END_REF] ; a pooled analysis of the two studies supported the presence of an IL4 x IL4R interaction, with an adjusted pooled IOR of 2.09 [1.33-3.28], p=0.001. The IL4/IL4R signalling is implicated in human diseases including asthma, allergy, and atopic dermatitis [START_REF] Wang | Metabolic checkpoints in activated T cells[END_REF] . Interestingly, the Th2 cytokine IL4 also promotes pro-metastatic phenotypes such as enhanced tumour survival and proliferation [START_REF] Hallett | Cytokine Stimulation of Epithelial Cancer Cells: The Similar and Divergent Functions of IL-4 and IL-13[END_REF] , tumour growth [START_REF] Venmar | IL4 receptor α mediates enhanced glucose and glutamine metabolism to support breast cancer growth[END_REF] , tumour burden [START_REF] Venmar | IL4 Receptor ILR4 Regulates Metastatic Colonization by Mammary Tumors through Multiple Signaling Pathways[END_REF] in epithelial cancer cells, through the IL4R. Previous studies have also suggested a role of IL4 and its receptor gene in susceptibility to autoimmune diseases such as multiple sclerosis [START_REF] Zhang | Association of IL4 and IL4R polymorphisms with multiple sclerosis susceptibility in Caucasian population: A meta-analysis[END_REF] and rheumatoid arthritis [START_REF] Hussein | Association of interleukin-4 receptor gene polymorphisms with rheumatoid arthritis in Egyptian female patients[END_REF] . Further, several associations have been described between family history of autoimmune diseases and ALL [START_REF] Buckley | Multiple sclerosis in mothers of children with acute lymphoblastic leukemia[END_REF][START_REF] Till | Family studies in acute leukaemia in childhood: a possible association with autoimmune disease[END_REF][START_REF] Morrison | Multiple sclerosis risk markers in HLA-DRA, HLA-C, and IFNG genes are associated with sex-specific childhood leukemia risk[END_REF] .

In addition, two recent papers, a candidate study [START_REF] Semmes | Leveraging Genome and Phenome-Wide Association Studies to Investigate Genetic Risk of Acute Lymphoblastic Leukemia[END_REF] and a Genome Wide Association Study (GWAS) [START_REF] Vijayakrishnan | Identification of four novel associations for B-cell acute lymphoblastic leukaemia risk[END_REF] have identified ALL risk alleles in interferon regulatory factor (IRF). IRF-1 has been shown to play roles in the immune response [START_REF] Tanaka | Cooperation of the tumour suppressors IRF-1 and p53 in response to DNA damage[END_REF] , by suppressing transcription of the IL4 gene in Th2 cells [START_REF] Maruyama | A novel function of interferon regulatory factor-1: inhibition of Th2 cells by down-regulating the Il4 gene during Listeria infection[END_REF] . The implication of this association in the aetiology of ALL need further investigation. It has also been suggested that people with allergic symptoms may have an improved immune surveillance [START_REF] Romagnani | The increased prevalence of allergy and the hygiene hypothesis: missing immune deviation, reduced immune suppression, or both?[END_REF] . Allergic symptoms are associated with an immune system oriented towards the Th2 pathway, which could activate the humoral immune response mediated by B lymphocytes (IgE production) and eosinophils associated with a possible cytotoxic effect towards potential leukaemic clones [START_REF] Jensen-Jarolim | AllergoOncology: the role of IgE-mediated allergy in cancer[END_REF] . In addition, the findings of several studies on a potential association between IL10 and childhood ALL could be related to the role of T-regulatory lymphocytes (Treg) in controlling the immune responses and the secretion of IL10.

In summary, this study supports a role of IL4R-rs1801275 variant in the association between ALL and history of allergy and a gene-gene interaction between IL4 and IL4R variants. If confirmed, these results could help understand the pathological mechanisms under the reported inverse association between allergy and childhood ALL. Further analyses in different studies and populations are needed, as well as international consortia to help unravel these relationships.

TABLE 1 :

 1 Sociodemographic characteristics in cases and controls included in the whole ESTELLE study and in the subsample of genotyped children of European ancestry

				ESTELLE study				Genotyped sample
		Controls		ALL				Controls		ALL
		N=1421	%	N=629	%	OR	95%CI p	N=704	%	N=411	%	OR	95%CI	p
	Sex
	Boys	738 52	371 59			364	52	246 60
	Girls	683 48	258 41			340	48	165 40
	Age
	<1 year	196 14	19 3			83	12	14 3
	1-2 years	267 19	152 24			129	18	111 27
	3-4 years	272 19	146 23			134	19	95 23
	5-7 years	235 17	132 21			108	15	82 20
	8-9 years	86	6	61 10			49	7	37 9
	10-11 years	91	6	57 9			47	7	37 9
	12-14 years	274 19	62 10			154	22	35 9
	Parental professional
	category
	Intellectual/scientific
	jobs, managers	942 66	399 63	1.00 Ref.	513	73	283 69	1.00	Ref.
	Employees	295 21	138 22	1.10 0.87-1.40 ns	121	17	79 19	1.22	0.88-1.70 ns
	Workers and Services	184 13	92 15	1.18 0.88-1.56 ns	70	10	49 12	1.26	0.84-1.89 ns
	Mother's highest
	diploma
	< baccalaureate	398 28	184 29	1.11 0.88-1.39 ns	155	22	110 27	1.36	1.00-1.85 0.05
	baccalaureate	308 22	138 22	1.03 0.80-1.31 ns	146	21	75 18	0.91	0.66-1.28 ns
	> baccalaureate	714 50	306 49	1.00 Ref.	403	57	226 55	1.00	Ref.
	Missing	1		1				-		-
	Father's highest
	diploma
	< baccalaureate	555 39	225 36	0.90 0.72-1.27 ns	248	35	137 33	1.02	0.77-1.37 ns
	baccalaureate	269 19	116 18	0.92 0.70-1.21 ns	126	18	82 20	1.09	0.77-1.54 ns
	> baccalaureate	551 39	250 40	1.00 Ref.	317	45	179 44	1.00	Ref.
	Missing	46	3	38 6			13	2	13 3%
	Maternal age at birth
	(years)
	<25	147 10	99 16	1.72 1.26-2.35 <0.001	59	8	49 12	1.61	1.02-2.52 0.04
	25-29	455 32	216 34	1.18 0.93-1.49 ns	220	31	150 36	1.32	0.98-1.79 0.07
	30-34	506 36	212 34	1.00 Ref.	265	38	146 36	1.00	Ref.
	35 or over	313 22	102 16	0.74 0.56-0.98 0.04	160	23	66 16	0.72	0.50-1.03 0.07
	Place of residence at
	diagnosis
	Rural	577 41	247 39	1.00 Ref.	319	45	182 44	1.00	Ref.
	Intermediate	312 22	131 21	1.02 0.79-1.32 ns	161	23	86 21	1.02	0.73-1.42 ns
	Urban	525 37	249 40	1.18 0.95-1.47 ns	224	32	141 34	1.14	0.86-1.53 ns
	Missing	7		2				-		2
	Type of housing at
	birth
	Apartment	581 41	280 45	1.25 1.02-1.51 0.03	231	33	163 40	1.40	1.02-1.83 0.01
	House	826 58	340 54	1.00 Ref.	463	66	243 59	1.00	Ref.
	Farm	9	1	6 1	1.69 0.57-5.02 ns	6	1	4 1	-
	Other	5		3				4	1	1
	Birth order
	1	594 42	312 50	1.00 Ref.	282	40	202 49	1.00	Ref.
	2	496 35	212 34	0.77 0.62-0.96 0.02	253	36	148 36	0.78	0.59-1.03 0.08
	≥ 3	331 23	105 17	0.57 0.44-0.74 <0.0001	169	24	61 15	0.48	0.34-0.68 <0.0001
	Breastfeeding
	No	541 38	280 45	1.00 Ref.	255	36	202 49	1.00	Ref.
	Yes	880 62	349 55	0.80 0.66-0.98 0.03	449	64	209 51	0.57	0.44-0.74 <0.0001
	ns: p≥0.10,: Odds ratios (OR) and 95% confidence intervals (95%CI) estimated using a logistic regression model adjusted for age and sex

TABLE 2 :

 2 Associations between allergy history and ALL in the whole ESTELLE study and in the genotyped sample Odds ratios (OR) and 95% confidence intervals (95%CI) estimated using a logistic regression model adjusted for age, sex, maternal educational level, maternal age at child's birth, household socio-professional category, housing type, birth order, urban/rural status and breastfeeding

			ESTELLE study				Genotyped subsample
		Controls	ALL cases				Controls	ALL cases
		N=1421	N=629	OR	95% CI	p	N=704	N=411	OR	95% CI	p
	Any allergy
	No	961	416	1.00	Ref.		458	272	1.00	Ref.
	Yes	454	206	0.91	0.74-1.13	ns	244	135	0.86	0.65-1.14	ns
	Missing	6	7				2	4
	IgE-related allergy
	No	1126	504	1.00	Ref.		540	328	1.00	Ref.
	Yes	287	119	0.80	0.63-1.03	0.09	160	80	0.80	0.58-1.10	ns
	Missing	8	6				4	3
	Asthma
	No	1318	571	1.00	Ref.		656	376	1.00	Ref.
	Yes	99	54	1.15	0.80-1.65	ns	47	34	1.34	0.82-2.21	ns
	Yes, without treatment	1	2	-			0	2	-
	Yes, with treatment	96	52	1.13	0.78-1.64	ns	46	32	1.28	0.77-2.12	ns
	Antihistamines	60	23	0.79	0.47-1.32	ns	30	15	0.98	0.50-1.94	ns
	Corticosteroids	72	39	1.15	0.76-1.76	ns	38	23	1.17	0.66-2.07	ns
	Bronchodilators	92	51	1.16	0.80-1.69	ns	45	31	1.26	0.76-2.10	ns
	Missing	4	4				1	1
	Allergic rhinitis or
	sinusitis
	No	1310	593	1.00	Ref.		638	385	1.00	Ref.
	Yes	105	33	0.65	0.42-0.98	0.04	64	23	0.64	0.38-1.09 0.10
	Yes, without treatment	19	8	0.79	0.33-1.87	ns	10	5	0.70	0.22-2.21	ns
	Yes, with treatment	84	24	0.60	0.37-0.98	0.04	54	17	0.60	0.33-1.07 0.09
	Antihistamines	78	23	0.62	0.37-1.01	0.06	50	16	0.59	0.32-1.09 0.09
	Corticosteroids	45	9	0.41	0.20-0.87	0.02	29	6	0.37	0.15-0.94 0.04
	Missing	6	3				2	3
	Atopic dermatitis
	No	1311	585	1.00	Ref.		639	377	1.00	Ref.
	Yes	106	41	0.74	0.51-1.10	ns	64	32	0.82	0.51-1.32	ns
	Missing	4	3				1	2
	Eczema
	No	1192	534	1.00	Ref.		591	345	1.00	Ref.
	Yes	225	92	0.82	0.62-1.08	ns	113	63	0.94	0.66-1.35	ns
	Missing	4	3				-	3
	Food allergy
	No	1344	604	1.00	Ref.		662	396	1.00	Ref.
	Yes	73	23	0.62	0.38-1.02	0.06	40	14	0.53	0.27-1.01 0.06
	Missing	4	2				2	1
	Drug allergy
	No	1326	580	1.00	Ref.		652	374	1.00	Ref.
	Yes	95	48	1.11	0.76-1.62	ns	52	36	1.28	0.79-2.06	ns
	Missing	-	1				-	1
	Desensitisation
	No	1405	623	1.00	Ref.		698	406	1.00	Ref.
	Yes	13	6	1.08	0.39-2.96	ns	6	5	1.34	0.37-4.80	ns
	Missing	3	-				-	-
	ns: p≥0.10;

TABLE 3 :

 3 Associations between candidate alleles of Th2 cytokines and childhood ALL, genotyped sample of 411 ALL cases and 704 controls

		Controls (N=704)		ALL cases (N=411)
		n	%	n	%	OR 95% CI	p
	IL13-rs20541
	GG	437	62.3	248	64.4	1.00 Ref.
	AG	240	34.2	123	31.9	0.92 0.68-1.20	ns
	AA	24	3.4	14	3.6	0.91 0.45-1.91	ns
	missing	3		26
	AG+AA vs GG	264	37.7	137	35.6	0.91 0.69-1.20	ns
	IL4-rs2070874
	CC	495	70.7	297	74.4	1.00 Ref.
	CT	190	27.1	97	24.3	0.85 0.63-1.16	ns
	TT	15	2.1	5	1.3	0.63 0.21-1.88	ns
	missing	4		12
	CT+TT vs CC	205	29.3	102	25.6	0.84 0.62-1.13	ns
	IL4-rs2243250
	CC	483	68.8	290	72.0	1.00 Ref.
	CT	203	28.9	107	26.6	0.89 0.66-1.20	ns
	TT	16	2.3	6	1.5	0.73 0.27-2.02	ns
	missing	2		8
	CT+TT vs CC	219	31.2	113	28.0	0.88 0.66-1.18	ns
	IL4 haplotype
	No TT haplotype	496	71.0	297	75.0	1.00 Ref.
	≥1 TT	203	29.0	99	25.0	0.83 0.61-1.12	ns
	missing	5		15
	IL10-rs1800896
	CC	157	22.5	85	21.6	1.00 Ref.
	CT	342	48.9	187	47.6	1.02 0.73-1.43	ns
	TT	200	28.6	121	30.8	1.10 0.75-1.60	ns
	missing	5		18
	CT+TT vs CC	542	77.5	308	78.4	1.05 0.76-1.44	ns
	IL10-rs1800871
	GG	424	60.6	221	55.1	1.00 Ref.
	AG	239	34.1	159	39.7	1.28 0.97-1.68	0.08
	AA	37	5.3	21	5.2	1.32 0.72-2.41	ns
	missing	4		10
	AG+AA vs GG	276	39.4	180	44.9	1.28 0.98-1.67	0.07
	IL10-rs1800872
	GG	426	60.9	224	55.9	1.00 Ref.
	GT	239	34.1	156	38.9	1.22 0.93-1.62	ns
	TT	35	5.0	21	5.2	1.42 0.77-2.62	ns
	missing	4		10
	GT+TT vs GG	274	39.1	177	44.1	1.25 0.95-1.63	ns
	IL10 haplotype
	No TAT haplotype	422	61.0	215	55.7	1.00 Ref.
	≥1 TAT	270	39.0	171	44.3	1.27 0.97-1.67	0.08
	missing	12		25
	IL4R-rs1801275
	AA	433	61.9	242	61.7	1.00 Ref.
	AG	231	33.0	134	34.2	1.03 0.78-1.37	ns
	GG	36	5.1	16	4.1	0.80 0.42-1.54	ns
	missing	4		19
	AG+GG vs AA	267	38.1	150	38.3	1.00 0.76-1.31	ns
	ns: p≥0.10; Odds ratios (OR) and 95% confidence intervals (95%CI) estimated using a logistic regression model
	adjusted for age, sex, maternal educational level, maternal age at child's birth, household socio-professional
	category, housing type, birth order, urban/rural status and breastfeeding

TABLE 4 :

 4 Gene-gene interaction analyses between candidate alleles of the Th2 cytokines pathway and ALL, genotyped sample of 411 ALL cases and 704 controls OR) and 95% confidence intervals (95%CI) estimated using a logistic regression model adjusted for age, sex, maternal educational level, maternal age at child's birth, household socio-professional category, housing type, birth order, urban/rural status and breastfeeding; pint: p for interaction test

	Without interaction		With interaction
	OR	95% CI	OR	95% CI	p int

TABLE 5 :

 5 Interaction analyses between the candidate polymorphisms and a reported history of allergy, in childhood ALL. : p for interaction test. ns: p≥0.10; Odds ratios (OR) and 95% confidence intervals (95%CI) estimated using a logistic regression model adjusted for age, sex, maternal educational level, maternal age at child's birth, household socio-professional category, housing type, birth order, urban/rural status and breastfeeding

		Any Allergy		IgE-related allergy		Asthma				Allergic rhinitis		Eczema				Atopic dermatitis
		OR	95% CI	pint	OR	95% CI	pint	OR	95% CI	pint	OR	95% CI	pint	OR	95% CI	pint	OR	95% CI	pint
	IL13-rs20541
	≥1 variant allele vs none	0.99	0.70-1.39		0.91	0.66-1.24		0.93	0.70-1.24		0.92	0.69-1.23		0.95	0.71-1.29		0.88	0.66-1.18
	Medical history vs none	0.91	0.64-1.30		0.77	0.51-1.17		1.46	0.78-2.72		0.67	0.34-1.31		1.01	0.63-1.62		0.69	0.37-1.30
	Variant allele x medical history	0.81	0.45-1.45	ns	1.06	0.53-2.09	ns	0.70	0.24-2.08	ns	0.96	0.32-2.85	ns	0.75	0.35-1.62	ns	1.57	0.59-4.15	ns
	IL4 TT haplotype
	≥1 variant allele vs none	1.06	0.73-1.53		0.90	0.64-1.27		0.82	0.60-1.12		0.83	0.61-1.15		0.89	0.64-1.24		0.81	0.59-1.11
	Medical history vs none	1.00	0.72-1.39		0.87	0.60-1.27		1.23	0.69-2.19		0.67	0.36-1.26		0.98	0.64-1.51		0.73	0.41-1.30
	Variant allele x medical history	0.49	0.25-0.93	0.03 0.68	0.32-1.45	ns	1.25	0.38-4.10	ns	1.03	0.34-3.16	ns	0.61	0.26-1.44	ns	1.38	0.49-3.93	ns
	IL10 TAT haplotype
	≥1 variant allele vs none	1.42	1.01-1.98		1.26	0.93-1.72		1.27	0.96-1.69		1.31	0.99-1.74		1.34	1.00-1.80		1.20	0.90-1.59
	Medical history vs none	0.97	0.67-1.41		0.79	0.51-1.21		1.32	0.70-2.50		0.77	0.40-1.47		1.05	0.65-1.70		0.54	0.27-1.06
	Variant allele x medical history	0.77	0.44-1.37	ns	1.11	0.57-2.15	ns	1.21	0.44-3.35	ns	0.63	0.21-1.91	ns	0.71	033-1.50	ns	2.33	0.88-6.23	0.09
	IL4R-rs1801275
	≥1 variant allele vs none	1.24	0.88-1.73		1.11	0.82-1.52		1.11	0.84-1.48		1.09	0.82-1.45		1.10	0.82-1.47		0.96	0.72-1.27
	Medical history vs none	1.07	0.74-1.53		0.96	0.62-1.47		2.27	1.21-4.25		0.93	0.46-1.91		1.15	0.72-1.83		0.62	0.32-1.21
	Variant allele x medical history	0.53	0.30-0.96	0.03 0.65	0.34-1.27	ns	0.23	0.08-0.71 0.008	0.41	0.14-1.22	ns	0.47	0.21-1.03	0.06 1.66	0.62-4.43	ns

pint

Acknowledgments

We are grateful to the paediatric oncologists of the SFCE (Société Française de lutte contre les Cancers et les Leucémies de l'Enfant et de l'Adolescent) for their help in recruiting the patients, and to the members of the INSERM team of Epidemiology of childhood and adolescent cancers and of the French national registry of childhood cancers for their contribution to the identification, recruitment, coding and interviews of the cases and controls. We thank the IPSOS institutes for their valuable service in recruiting the controls and performing the interviews, the Centre de

Funding

The ESTELLE study was supported by INCa, Ligue Nationale contre le Cancer, association Enfants et Santé, ANSES, the Agence Nationale de Sécurité Sanitaire de l'alimentation, de l'Environnement et du Travail (PNREST Anses, Cancer TMOI AVIESAN, 2013/1/248), INCa-DHOS, Cancéropôle Ile de France, ANR (Grant id : ANR-10-COHO-0009). Audrey Bonaventure was supported by a fellowship from the Fondation ARC pour la Recherche sur le Cancer (PDF20190508759). Roula Ajrouche was supported by a fellowship from the Lebanese University. Ghinaj Chandab was supported by a fellowship from INSERM.

Funders had no involvement in the study design, data analysis, and interpretation of the results.

Data availability statement

The data that supports the findings of this study are available from the corresponding author upon reasonable request.

Conflict of Interest statement

The authors declare no potential conflict of interests.

Authors' contribution

AP, MS, BN, GP, GM, CH and JC contributed to data acquisition. JC designed the study. RA, GC, JC and AB designed the analyses. RA and GC performed the analyses. RA, GC, JC and AB participated in data interpretation and drafted the manuscript. All authors critically revised the manuscript.