To the Editor,

Asthma and rhino-conjunctivitis (RC) are common diseases worldwide that are frequently associated. Observed differences in prevalence of asthma and RC may be explained by genetic susceptibility, though environmental factors play a relevant role [1]. In order to increase genomic information on Sicilian children, this research has explored some genetic variants to discover possible association with asthma and RC.

A representative sample of 1050 children within the “Palermo Junior High School” (PJHS II) [2] study were investigated through questionnaires, spirometry, and skin prick test (SPT) to quantify the prevalence of asthma and RC, in association with allergic sensitization and respiratory function, and to evaluate the role of environmental and host risk factors for allergic respiratory diseases. The study was approved by the local Institutional Ethical Committee. All parents of the enrolled children signed a written informed consent.

Two different phenotypes were identified: Current Asthma (CA) defined as asthma ever plus at least a wheeze episode in the last 12 months, RC defined as sneezing, or runny, or blocked nose apart from common cold or flu in the last 12 months and nose problem accompanied by itching and/or watering eyes. The concomitant presence of CA and RC was merged into the CA group; children without CA and RC (nAnRC) were used as controls.

A total of 52 Single Nucleotide Polymorphisms (SNPs), involved in the innate immune system pathways were selected for genotyping by Matrix-Assisted Laser Desorption/Ionization (MALDI-TOF-MS). Out of the 52 initially selected SNPs, 7 were complete drop-outs and the remaining SNPs were successfully genotyped. The individuals were genotyped with the Illumina Bead-Chip (Illumina Inc., San Diego, CA, USA); the PLINK v1.07 software was used to perform standard quality control. SNPs were excluded if they had low call rates (proportion of genotyped called < 90%), were not in Hardy-Weinberg equilibrium (HWE, p < 0.001) on the nAnRC subjects, or had a low minor allele frequency (MAF < 1%). A total of 22 SNPs were used for further analyses.

Mean values were compared among children with CA, RC and nAnRC using the analysis of variance (ANOVA). Differences of categorical variables were evaluated using Chi-squared test. Associations between single SNPs and CA and RC were analysed by applying the case/control model of the SNPassoc R package, adjusting for sex, age, body mass index (BMI), SPT+ (at least one positive), exposure to current environmental tobacco smoke and traffic.

The demographic and lung function characteristics of the 1050 subjects are shown in Table 1. The study sample was composed by 523 (49.8%) Female and 527 (50.2%) Male, aged 12.07 ± 0.74 years on average. Subjects were categorized into CA (n = 61), RC (n = 184) and nAnRC (n = 805). Subjects with CA and RC more frequently had SPT+; subjects with CA were younger than nAnRC and RC subjects.

Table 1 Baseline demographic and clinical characteristics of study population
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Chromosome, gene, SNP name, quality control tag, alleles coding (Major/minor), minor allele frequency (MAF), test for Hardy-Weinberg Equilibrium, percentage of missing values (%) and genotyping distribution are reported in Table 2.

Table 2 Characteristics of the 52 Single Nucleotide Polymorphisms (SNPs)
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By applying the case/control model, no SNP reached the Bonferroni corrected significance threshold (P value < 0.002, i.e., 0.05/#tests), and only one SNP reached the Bonferroni corrected suggested significance threshold (P value < 0.005, i.e., 0.10/#tests). However, we also included those SNPs reaching the nominal significance threshold (P value < 0.05) just to highlight modest associations with the two studied phenotypes. CA was strongly associated only with rs4252665 and modestly with rs1801275 and rs17616434; RC was modestly associated with rs7741835, rs8079416, rs3859192, rs3894194 and rs7212938. Table 3 shows the genotypic frequencies of the associated SNPs in CA/RC and nAnRC groups, and the adjusted OR and 95% CI from the logistic regression model for the only SNP strongly associated. The SNP rs4252665 showed significantly different genotypic frequencies between the two groups, i.e., the CA subjects had a high frequency of CT heterozygote genotype compared with nAnRC, which were mostly homozygous. Indeed, using the overdominant genetic model, in which the baseline is the homozygous genotype (CC/TT), the CT genotype of rs4252665 showed a large increased risk of CA (ORC/T = 5.75; 95% CI = 2.03–16.29). The SNPs modestly associated with CA showed a high frequency of the major allele homozygote genotype compared with nAnRC, in which the genotypes were mostly characterized by the presence of the minor allele. Furthermore, with respect to nAnRC, SNPs modestly associated with RC showed small variations in the genotypic frequencies. In particular, the SNPs rs8079416, rs7741835 and rs3894194 showed high frequencies of heterozygote genotypes compared with nAnRC, which are frequently homozygous, whilst the SNPs rs7212938 and rs3859192 had high frequencies of the minor allele homozygote genotypes compared with nAnRC, in which genotypes are characterized by the presence of the major allele.

Table 3 Genotypic frequencies of the associated SNPs in CA/RC and nAnRC groups
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The detected association signals for CA were located within the Toll-like receptor (TLR1) on chromosome 4, the interleukin 4 receptor (IL4R) on chromosome 16 and the Erb-b2 receptor tyrosine kinase 2 (ERBB2) on chromosome 17. It is known that Toll-like receptors (TLRs) represent a major group of receptors for the specific recognition of pathogen-associated molecular patterns of microbes capable of activating innate and adaptive immunity that reduce the risk for asthma [3]. The IL4R gene is known to encode a protein that regulates IgE production and it has been shown that allelic variations in this gene are associated with atopy, allergic rhinitis and asthma [4]. Recently, some loci of ERBB2, which belong to the encoding region 17q12, have been reported to be in linkage disequilibrium with loci in the region 17q21 encoding gasdermin A (GSDMA) gene, previously associated with childhood asthma [5,6,7].

With regard to the RC, the modestly associated genes were interleukin 17 (IL17) on chromosome 6, leucine rich repeat containing 3C (LRRC3C), and GSDMA on chromosome 17. IL17 is a pro-inflammatory cytokine that targets epithelial cells48 and its expression in the nasal mucosa has been associated with allergic rhinitis and its degree of severity [8, 9]. To our knowledge, no functional studies have been published on LRRC3C, although, within the human genome, the gene LRRC32 has been associated with eczema and allergic rhinitis [10], and probably some similarities between the two proteins encoded by LRRC3C and LRRC32 exist. Finally, GSDMA gene has been associated with childhood asthma and allergic disease in many populations. In particular, region 17q21 has been originally identified in the first GWAS on childhood asthma [6], and GSDMA variants were suggested to be strong risk factors for asthma and airway inflammation [7].

Overall, our findings reveal the importance of different genetic variants at 4p14, 16p12.1 17q12, 6p12.2 and 17q21.1, identifying possible candidate genes responsible for CA and RC in the Sicilian child population. These results are a preliminary step in understanding the pathophysiology of asthma and rhino-conjunctivitis in a paediatric population in the Mediterranean area and need to be verified by further studies using more advanced technologies. Furthermore, novel methodologies combining genome-wide association study (GWAS; [11]) and expression quantitative trait locus (eQTL [12]) such as summary-data based Mendelian randomization (SMR; [13]), PrediXcan [14], MetaXcan [15], would be useful in discovering new genetic variants linked to these allergic respiratory diseases in this geographic area. Unlike traditional single-variant tests, these innovative approaches based on SNP-gene linkage will provide valuable insights on disease causality. Noteworthy, the integrative analysis of GWAS and eQTL studies, by identifying gene-trait-associated changes in the expression, would mitigate some tasks associated with a GWAS approach, allowing the discover of genetic variants which can affect gene expression [16]. Moreover, since some gene functions are often pleiotropic, this combined approach would allow a better comprehension of the pathways through which pleiotropy can affect clinical phenotypes.

In conclusion, the present study could facilitate the application of novel therapeutics and preventive strategies arising from the genomics era of precision medicine.