Supplementary Methods/Results

Supplementary methods/results

Genotyping

We screened a total of 19 loci for atopic dermatitis reaching the genome-wide significance threshold of P < 5 × 10-8: 1q21 (FLG), 11q13.5 (C11orf30/LRRC32), 5q22.1 (TMEM232/SLC25A46), 20q13.33 (TNFRSF6B/ZGPAT), 11q13.1 (OVOL1), 19p13.2 (ACTL9), 5q31.1 (KIF3A/IL13), 2q12 (IL1RL1/IL18R1/IL18RAP), 3p21.33 (GLB1), 3q13.2 (CCDC80), 6p21.3 (GPSM3 [MHC region]), 7p22 (CARD11), 10q21.2 (ZNF365), 11p15.4 (OR10A3/NLRP10), 20q13 (CYP24A1/PFDN4), 4q27 (IL2/IL21), 11p13 (PRR5L), 16p13.13 (CLEC16A/DEXI) and 17q21.32 (ZNF652).E1-5 It is known that there are differences in linkage disequilibrium in the associated loci among ethnic groups and statistically significant peaks of GWAS are different between populations. In our previous GWAS, we presentedassociation results for the GWAS-reported regions of atopicdermatitis.E4 In this study, we assessed seven SNPs thathadthe top signals in our previous GWAS for atopic dermatitis, at the FLG, C11orf30/LRRC32, TMEM232/SLC25A46, TNFRSF6B/ZGPAT, OVOL1, ACTL9 and KIF3A/IL13 loci.E4We finally examined a total of 19 SNPs in the susceptibility loci for atopic dermatitis (Table E1).

Recent GWASs for eosinophilic esophagitis have identified a total of seven susceptibility loci, and we investigated seven SNPs, the top signals in the reported GWAS with genome-wide significance (P < 5 × 10-8): 5q22 (TSLP/WDR36), 2p23 (CAPN14), 8p23 (XKR6), 15q13 (LOC283710/KLF13), 11q13.5 (C11orf30), 12q13.3 (STAT6) and 19q13.11 (ANKRD27). E6-8

It has been shown that mutations in FLGare the most significant risk factor for AD and also confer risk for FA. We further assessed the associations of FLG mutations with AD. We genotyped a total of sixFLG null variants, c.3321delA, p.Q1701*, p.S2554*, p.S2889*, p.S3296* and p.K4022*,which have been reported in Japanese populations.7,E9

Genomic DNA was extracted with standard protocols and SNPs were genotyped using the multiplex PCR-based Invader assay (Hologic), the TaqMan assay (Thermo Fisher Scientific) or the PCR-direct sequencing method.

Study population

Subjects with childhood food allergy (FA) were recruited from three hospitals: the National Sagamihara Hospital for primary analysis, and the Aichi Children's Health and Medical Center, and Osaka Prefectural Medical Center for Respiratory and Allergic Diseases for validation analysis. All case subjects had a diagnosis of FA by a pediatric specialist according to the current Japanese guideline.E10-12 FA was diagnosed by positive oral food challenge or a definitive clinical history after food intake. Characteristics of the cases are shown in Table E2. Healthy volunteers who had never been diagnosed with bronchial asthma and/or atopic dermatitis were recruited. The985subjects studied for primary analysis were from Tsukuba University,and the904 for validation analysisweremembers of the Rotary Club of Osaka-Midosuji District 2660 Rotary International in Japanand Fukui University.E4 All participants in this study were Japanese and gave written informed consent to participate in the study. The ethical committees of the hospitals and the Institute of Physical and Chemical Research (RIKEN) approved this study.

Statistical analysis

We performed an association study using a primary set of 593 FA cases and 985 controls, followed by validation of the results in an independent set of 279 cases and 886 controls. We assessed associations of the genetic variants between case and control subjects by using the Cochran-Armitage Trend test. We also calculated odds ratios (ORs) with 95 percent confidence intervals (95% CI) from a two-by-two allele frequency table. Combined analysisusing the primary and validation data sets was conducted using the Mantel-Haenszel method, and we examined heterogeneity across the primary and validation studies by the Breslow-Day test. Statistical significance was set at P < .05.

We performed logistic regression analysis adjusted for sex. We combined the data under the fixed effects model by using GWAMA ver. 2.1.We used the R package (ver. 3. 2. 3) for these statistical analyses.P values of less than0.05 were judged to be significant. Linkage disequilibrium was calculated by using Haploview 4.2 software and genotype data from HapMap.Stratified analyses were conducted for the cases by comorbidity of atopic dermatitis.

The possible biases

We did not use age and sex-matched controls, and the controls were significantly older. It has been suggested that sex and age are related to allergic phenotypes. We performed linear regression analysis between age and allele frequencies of all examined SNPs in the primary and validation control populations, and confirmed that the R-squares of all SNPs were less than 0.01 (R2 < 0.01). There was no evidence of association between age and allele frequencies. However, we used adult controls, and some of the controls might not have remembered having AD in childhood given the fact that most AD is transient. Furthermore, we have no information regarding EoE and/or FA in control individuals, which suggests that some of the controls might have had EoE and/or FA. If control subjects had had childhood AD, EoE or FA, it might have affected the results as a potential bias. However, those limitations would seem to lead to underestimation of the impact of variants in our study. Furthermore, we conducted logistic regression analysis adjusted for sex and found that this did not markedly change the results (Table E4). The causal gene is sometimes located far away on the genome across multiple linkage disequilibrium (LD) blocksE13. However, the 14 susceptibility loci might contain candidate genes for childhood FA.

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