Characterising the allergen landscape in paediatric allergic rhinitis and/or asthma

Abstract

Objective

To characterise the allergen sensitisation profile and its demographic, seasonal and laboratory associations in children with allergic rhinitis (AR) and/or asthma in Guangdong, China.

Methods

We retrospectively reviewed the records of children diagnosed with AR and/or asthma from January 2020 to December 2023. Serum allergen-specific Immunoglobulin E (IgE) measurements were used to identify allergens. Sensitisation patterns and their relationships with age, sex, season of visit, peripheral-blood cell counts and immune markers were assessed with χ² tests and Spearman correlation.

Results

A total of 8080 children (median age, 7.0 years; 69.0% boys) were included; 89.1% had AR, 7.5% asthma and 3.4% both conditions. Overall, 76.5% were sensitised to inhalant allergens, 18.3% to food allergens and 5.2% to other allergens. Dermatophagoides farinae (93.2 %) and Dermatophagoides pteronyssinus (88.3 %) were the dominant inhalant allergens, whereas egg (14.2 %) and milk (11.9 %) prevailed among foods. Dual sensitisation was most common (67.6 %). Inhalant sensitisation peaked in summer (79.8 %), whereas food sensitisation was highest in spring (6.8 %). Inhalant‐allergen positivity increased with age, while food‐allergen positivity declined (p<0.001). Seventeen of 18 allergens displayed significant sex differences. Total IgE correlated positively with most inhalant and food allergens but negatively with egg allergen (p<0.05); neutrophil percentage showed similar positive correlations with several allergens. Allergen sensitisation correlates with impaired lung function and elevated airway inflammation.

Conclusion

House-dust mites are the principal sensitising allergens in children with AR and/or asthma in Guangdong, followed by egg and milk. Sensitisation patterns are modulated by season, age and sex, underscoring the necessity for region- and age-specific preventive and therapeutic strategies in paediatric allergic disease management.

WHAT IS ALREADY KNOWN ON THIS TOPIC

• Allergic rhinitis (AR) and asthma are common in Chinese children, but links between specific allergen profiles with season, age, sex, lung function and immune markers are poorly defined.

WHAT THIS STUDY ADDS

• Analysed allergen-specific IgE results from 8080 Guangdong children with AR and/or asthma.

• Sensitisation patterns varied by sex, age and season and were strongly linked to lung function.

HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY

• Provide Guangdong-specific allergen exposure data to tailor prevention and treatment for paediatric AR/asthma.

Introduction

AR and asthma are prevalent allergic conditions where allergens play a crucial role in pathogenesis.^{1 2} These diseases significantly affect patients’ quality of life and pose substantial socioeconomic burdens.³ Epidemiological data indicate a worrying rise in paediatric allergic diseases, particularly in AR-asthma comorbidity.^{4 5}

AR is a chronic IgE-mediated inflammatory disorder primarily affecting the upper respiratory tract.⁶ Exposure to aeroallergens, such as pollen and mites, triggers immune hypersensitivity, leading to excessive IgE production and nasal mucosal inflammation.⁶ AR commonly appears early in life, affecting over 5% of children by age three. The International Study of Asthma and Allergies in Childhood (ISAAC), spanning 236 centres in 98 countries, reports an increase in AR prevalence from 8.5% in children aged 6–7 to 14.6% in adolescents aged 13–14⁷. In China, AR is the leading inflammatory respiratory condition in children, with a prevalence rate of 15.79%.⁸

Asthma, a chronic inflammatory airway disease triggered by allergens,⁹ is characterised by reversible bronchoconstriction and airway hyperresponsiveness, affecting primarily the lower respiratory tract.¹⁰ The Global Asthma Report highlights a worldwide asthma prevalence of 9.1% in children, 11.0% in adolescents and 6.6% in adults.¹¹

AR and asthma are interconnected respiratory diseases stemming from dysregulated immune responses to antigens. The ‘same airway, same disease’ concept suggests that untreated AR can progress to asthma, and individuals with asthma often exhibit AR symptoms.^{7 12} A decade-long paediatric cohort study¹³ revealed a 10.17% incidence of AR-asthma comorbidity, emphasising the need for early intervention.

This study conducted a retrospective cohort analysis of 8080 paediatric patients with AR and/or asthma from Guangdong, China. Our objective is to delineate the region-specific allergen distribution and explore correlations between serum allergen-specific IgE levels and related laboratory indicators. These findings aim to optimise diagnostic and therapeutic strategies in paediatric allergy management.

Methods

Patients and study design

We recruited 8080 paediatric patients diagnosed with AR and/or asthma, who underwent allergen testing between January 2020 and December 2023 at the Guangzhou Women and Children Medical Centre, Guangzhou Medical University (National Regional Medical Centre). Specific IgE antibodies against 18 allergens were detected using a fluorescent immunoassay in patient sera. Inclusion criteria included patients aged 0.5 to 14 years at consultation, a first-time AR and/or asthma diagnosis aligned with the corresponding diagnostic criteria and guidelines,¹⁴,¹⁷ and a positive serum sIgE test for at least one allergen. Patients with other chronic respiratory and immunological diseases, as well as those with other comorbidities such as severe hepatic and renal dysfunction, digestive disorders, infectious diseases and dysplasia, or those with missing data, were excluded. Informed consent was obtained from all participants or their guardians. Ultimately, we enrolled 8080 eligible children from an initial pool of 27 408 patients. However, the results of the study will be disseminated to relevant stakeholders, including clinicians and healthcare policy-makers, to inform future clinical practice. The study received approval from Guangzhou Women and Children’s Medical Center’s Ethics Committee ([2023]097B01) and adhered to the Helsinki Declaration. The study flowchart is provided in figure 1.

Figure 1. Flowchart of patient selection and study design.

Patient and public involvement

Patients or the public were not involved in the design, or conduct, or reporting, or dissemination plans of our research.

Research methodology

Venous blood was collected into tubes with clot activator, allowed to sit at room temperature for 1 hour, then centrifuged at 3000×g for 10 min to extract serum for sIgE quantification. The ALLEOS 2000^TM allergen detection system (Hycor Biomedical, USA) was used for standardised specific immunoglobulin E (sIgE) measurement, based on fluorescent magnetic microparticle chemiluminescence. The sIgE levels were measured in units of kU/L, ranging from 0 to 100 kU/L. sIgE levels were graded into categories from 0 to 6: level 0 (<0.35 kU/L), level 1 (≥0.35 to <0.70 kU/L), level 2 (≥0.70 to <3.50 kU/L), level 3 (≥3.50 to <17.50 kU/L), level 4 (≥17.50 to <50.00 kU/L), level 5 (≥50.00 to <100.00 kU/L) and level 6 (≥100.00 kU/L). Levels 1–2 indicate mild sensitisation, levels 3–4 moderate sensitisation and levels 5–6 severe sensitisation. Tested allergens included inhaled allergens: Dermatophagoides farinae (Der. farinae), Dermatophagoides pteronyssinus (Der. pteronyssinus), cat epithelium and dander, dog epithelium and dander, German cockroach, common mugwort and weed pollen allergens (daisies, dandelions, plantain, quinoa, gooseberries); ingested allergens included the following: egg white, peanut, soya bean, milk, crab, shrimp, egg, fish and wheat; other allergens included the following: fungal allergens and Aspergillus fumigatus (Penicillium terreus, Mycosphaerella, Aspergillus fumigatus, Pseudomonas albicans, Streptomyces, Helicobacter longum). Multiple sensitisation was defined as positive sIgE to two or more allergens tested. A total of 18 allergens were assayed. The panel was compiled on the basis of regional epidemiology, clinical relevance for paediatric respiratory and allergens and routine availability in the hospital laboratory.

Demographic stratification

Participants were grouped by sex (male vs female) and age, which was categorised into three developmental stages: infancy (0–2 years), preschool (3–6 years) and school-age (7–14 years). Within each age group, comparisons were made for allergen positivity rates (any inhalant, any food and their respective categories) and diagnostic phenotypes (AR, asthma and AR+asthma). Seasons were defined according to the World Meteorological Organization criteria: spring (March–May), summer (June–August), autumn (September–November) and winter (December–February). The proportion of positive cases within each season was analysed. In terms of disease diagnosis, patients were divided into three clinical groups—AR alone, asthma alone and AR combined with asthma—to examine the relationships between allergen positivity rates and disease types. The dataset did not include socioeconomic characteristics and environmental exposures (eg, parental education, household income, household tobacco smoke exposure, pet ownership, visible damp/mould, cooking fuel type and ambient air-pollution metrics such as PM_2.5/NO₂), and thus, these variables were not included in the analysis.

Statistical analysis

In this study, statistical analysis was performed using SPSS 28.0, and data were visualised with GraphPad Prism 10.0. Continuous data were presented as either mean±SD or median (Q25, Q75), depending on normality, while count data were expressed as n (%). Group comparisons were conducted using the Pearson χ² test, and correlations were evaluated using Spearman’s rank correlation test. In the subset of children with available spirometry and fractional exhaled nitric oxide (FeNO) data, we assessed the clinical relevance of sensitisation by calculating Spearman’s correlation coefficients between each allergen and pulmonary function indices, including forced vital capacity (FVC) (% predicted), forced expiratory volume in 1 s (FEV1) (% predicted), FEV1/FVC (% predicted) and peak expiratory flow (PEF) (% predicted), as well as FeNO. Correlation coefficients (r) and exact p values were reported where applicable, with statistical significance defined as two-sided p<0.05.

Results

Demographic characteristics of the study population

This study involved 8080 paediatric patients, with a median age of 7.00 years (5.33, 9.00). The cohort included 5577 males (69.02%) and 2503 females (30.98%). By developmental stage, 306 infants (<3 years; 3.79%), 3331 preschoolers (3–5 years; 41.22%) and 4443 school-aged children (≥6 years; 54.99%) were enrolled. Initial diagnoses revealed AR as the most prevalent (n=7195, 89.05%), followed by asthma (n=608, 7.52%), with the lowest incidence in AR-asthma comorbidity (n=277, 3.43%) (online supplemental table S1).

Sensitisation pattern of allergens

In our cohort of 8080 cases, the highest sIgE positivity was for inhalant allergens at 76.51% (6182/8080), followed by ingested allergens at 18.33% (1481/8080) and other allergens at 5.16% (417/8080) (figure 2A). Notably, dual-allergen sensitisation dominated at 67.60% (5462/8080), significantly higher than monosensitisation (9.77%, 790/8080), trisensitisation (11.40%, 921/8080) and tetrasensitisation (5.80%, 469/8080). Higher-order sensitisations, including pentasensitisation (2.74%, 221/8080) and polysensitisation to six or more allergens (2.69%, 217/8080), accounted for a combined 5.43% (figure 2B). Among specific allergens, Der. farinae and Der. pteronyssinus exhibited the highest positive rates at 93.18% and 88.27%, respectively, followed by egg (14.18%), milk (11.89%), German cockroach (5.75%) and cat dander (3.70%). Plant-derived allergens, especially common mugwort, exhibited minimal reactivity, a finding that diverges sharply from the allergen landscape reported in northern China (figure 2C).

Figure 2. Distributional characteristics of allergens in 8080 children. (A) The three main types of allergens in children; this pie chart shows the three main types of allergens in this study. Blue represents inhalant allergens, red represents food allergens and grey represents other types. (B) Distribution of positive allergen counts among 8080 paediatric patients, showing the corresponding number of cases for each category of allergen positivity (1–6), with darker colours indicating a higher number of positive allergen types. (C) Classification of 18 common allergens in children. (D) Distribution of sensitisation levels of 18 allergens in children. This tiered chart displays the categorised detection values for the 18 allergens, where darker shades represent more severe sensitisation levels, defined as follows: level 0: <0.35, level 1: 0.35–0.7, level 2: 0.7–3.5, level 3: 3.5–17.5, level 4: 17.5–50, level 5: 50–100 and level 6: >100. (E) This Venn diagram shows the overlap between the first four inhalant allergens. (F) This figure shows the intersection of the top four ingested allergens. (G) Number of positive cases of allergen species in children with AR and/or asthma. AR, allergic rhinitis.

Class analysis of sIgE to the 18 allergens revealed distinct intensity patterns (figure 2D). Der. farinae and Der. pteronyssinus were characterised by high-grade sensitisation: almost 90% of positive sera fell into levels 3–6 (≥3.5 kU/L). In contrast, the principal food allergens like egg white, wheat and milk were confined largely to levels 1–2 (0.35–3.49 kU/L), indicative of low-grade reactivity. Sensitisation to Artemisia pollen showed values below 0.35 kU/L (level 0).

Co-sensitisation analyses underscored strong clustering within the dominant allergen groups. Among inhalants, concomitant positivity for Der. farinae and Der. pteronyssinus occurred in 90.36% (6,413/7097) of children with multiple inhalant sensitisations (figure 2E). For food allergens, simultaneous sensitisation to milk and egg was observed in 57.83% (491/849) of cases (figure 2F).

When the cohort was stratified by clinical diagnosis (AR alone, asthma alone and AR combined with asthma), Der. farinae and Der. pteronyssinus remained the predominant sensitising allergens in every group, with egg and milk ranking next in frequency (figure 2G), indicating a largely uniform sensitisation landscape across the three diagnostic categories.

Relationship between allergen sensitisation, month of visit, age and gender

To explore the correlation between allergens and demographic characteristics, we analysed 8080 cases based on consultation month, age and gender. Significant seasonal oscillations were identified in patient visits from 2020 to 2023, with a marked peak in July and August (figure 3A). Our analysis revealed that inhalant allergens peaked in summer (79.75%, 2702/3388), significantly exceeding other seasons. Ingested allergens showed the lowest positivity in summer (4.28%, 145/3388) but highest in spring (6.80%, 115/1691). Other allergens exhibited the lowest summer positivity (15.97%, 541/3388) and highest winter rate (21.23%, 234/1102) (online supplemental table S2).

Figure 3. Plot of allergens in children’s characteristics in relation to month and age. (A) The number of positive cases of allergens in different months of illness. This line graph represents the number of positive cases of AR, asthma and AR with asthma corresponding to each month between 2020 and 2023. (B) The bar chart representing the number of positive cases at different ages, illustrating how the count of allergen-positive cases changes with increasing age. (C) The tiered chart depicting the relationship between children of different ages and various allergen classifications, showing the proportion of the three different types of allergens at various ages among the 8080 paediatric cases.

Analysis of allergen positivity rates across age groups in this cohort revealed that patients aged 9–14 years constituted the largest group (67.09%, 5423/8080), with peak enrolment occurring at 10–11 years (12.64%, 1021/8080; figure 3B). Figure 4C depicts age-dependent sensitisation patterns. Inhaled allergens (blue) exhibited substantial growth and consistently remained dominant through age 14. In contrast, ingested allergens (red) showed an inverse correlation, declining from 90% aged 0–1 year to below 5% after age 6. Other allergens (grey) peaked earlier, declining after age 3. χ² tests confirm significant age-related shifts for all allergen classes (p<0.001), highlighting a transition from food-driven sensitisation in early childhood to inhalant predominance during school-age and adolescence. Positivity for inhaled allergens increased continuously, reaching 85.46% (3797/4443) in school-aged children (χ²=633.235). Conversely, ingested allergens mainly peaked in infancy and decreased significantly with age (χ²=602.746), as did other allergens (χ²=217.111) (online supplemental table S3). According to Spearman’s analysis, there is a positive correlation between the positive rates for inhalant and other types of allergens and age, whereas the positive rates for ingested allergens show a negative correlation with age (p<0.001) (online supplemental table S4).

Figure 4. Correlation between childhood allergens with immune indicators and cellular classification. (A) Allergens and cell classification. (B) Allergens and immune markers. Note: Cells display correlation coefficients (r); shading denotes direction and magnitude. *** indicates p<0.001; ** indicates p<0.01; * indicates p<0.05. BAS, basophil; EOS, eosinophil; FeNO, fractional exhaled nitric oxide; FEV₁, forced expiratory volume in 1 s; FVC, forced vital capacity; NEU, neutrophil; PEF, peak expiratory flow; IgM, Immunoglobulin M; IgA, Immunoglobulin A; IgE, Immunoglobulin E; IgG, Immunoglobulin G.

A further comparison of the positive rates for the 18 allergens across three age groups reveals that inhalant allergens, such as Der. farinae, Der. pteronyssinus, cat epithelium and dander, dog epithelium and dander and German cockroach, all exhibit a significant increase in positive rates with age. In contrast, ingested allergens, including peanuts, soya bean, milk, eggs and wheat, show a decrease in positive rates as age increases. The sIgE positive rates for egg whites and fish initially increase and then decrease (p<0.001) (online supplemental table S5).

Analysis of 8080 paediatric patients revealed gender-based differences in allergen positivity (p<0.001, online supplemental table S6). Further comparison of the positive rates of the 18 allergens between the two genders revealed that, except for Artemisia, all other 17 allergens had statistically significant differences in sIgE positive rates between male and female patients (p<0.001) (online supplemental table S7). Among male patients, the allergen with the highest sIgE positivity rate was Der. farinae, at 88.54%. For female patients, the highest IgE positivity rate was for Der. pteronyssinus, at 92.17%.

Correlation of allergens with cellular classification and immunological indicators

Of the 8080 children surveyed, 527 had at least one positive allergen result together with a complete leucocyte differential, and 321 had concomitant measurements of immunological markers. The Spearman correlation analysis was therefore applied to these two cohorts, respectively.

This revealed certain associations between the counts and percentages of different types of white blood cells and some allergens (figure 4A). Neutrophil count correlated positively with sIgE titres to Der. farinae. Neutrophil percentage showed broader positive correlations, correlating with Der. pteronyssinus, Der. farinae, dog epithelium and dander, German cockroach, weed pollen allergens, peanut, soya bean, crab, shrimp, wheat and fungal allergens, with p＜0.05. Similarly, a correlation analysis using Spearman’s method was performed between the immunological indicator test results of the 321 cases and the allergens. This uncovered certain correlations between some immune markers and specific allergens (figure 4B). Total IgE displayed strong positive correlations with Der. pteronyssinus, Der. farinae, cat epithelium and dander, dog epithelium and dander, German cockroach, weed pollen allergens, peanut, soya bean, crab, shrimp, wheat, Aspergillus fumigatus and fungal allergens, but IgE levels negatively correlated with egg allergens, with p＜0.05.

Clinical correlations between allergen sensitisation and airway function

Dust mite sensitisation (Der. pteronyssinus and Der. farinae) was negatively associated with FEV₁/FVC and PEF and positively associated with FeNO (p＜0.05), indicating links to airflow limitation and airway inflammation. Dog and cat dander sensitisation correlated positively with FeNO (p＜0.05). Food-specific IgE showed tentative associations with lung-function measures and FeNO, falling short of clear statistical significance. Aspergillus fumigatus sensitisation showed a strong negative correlation with FEV₁ (p＜0.05) (figure 5A). These results provide clinically meaningful associations between sensitisation patterns and objective markers of airway disease, thereby enhancing the interpretability of the findings.

Figure 5. Correlation between childhood allergens, cellular classification and immune indicators with airway dysfunction. (A) Airway dysfunction and allergens. (B) Airway dysfunction, both cell classification and immune indicators. Note: Cells display correlation coefficients (r); shading denotes direction and magnitude. *** indicates p<0.001; ** indicates p<0.01; * indicates p<0.05. BAS, basophil; EOS, eosinophil; FeNO, fractional exhaled nitric oxide; FEV₁, forced expiratory volume in 1 s; FVC, forced vital capacity; NEU, neutrophil; PEF, peak expiratory flow.

In figure 5B, it can be seen that eosinophils are negatively correlated with FVC, FEV₁ and FEV₁/FVC (r=−0.2731, p<0.001), while they are positively correlated with FeNO (r=0.2963, p<0.001). This indicates that eosinophils are associated with more severe asthma phenotypes. Basophils (BAS) are also negatively correlated with FEV1, but the correlation is weaker than that of eosinophils. The level of IgE is positively correlated with FeNO, which is consistent with the role of IgE in allergic responses. High IgE levels may be associated with more severe asthma symptoms and poorer lung function.

Discussion

This retrospective analysis of 8080 children with allergies in Guangdong, South China, characterises regional allergen exposure and its dynamic changes. The study group was largely composed of children with AR (89.05%), followed by those with asthma (7.52%) and AR with asthma (3.43%). Respiratory allergic disease occurrence was found to be primarily associated with allergen exposure, which varies regionally.^{6 18 19} For example, in Europe, birch-related pollen, mugwort and ragweed are major allergens for allergic diseases, while ragweed pollen is a major sensitiser in North America, affecting 26% of Americans.^{20 21} Pollen and mould dominate in Turkey.²² In China, Artemisia absinthium, Chrysanthemum fritillarum and plantain are predominant in the northwest, whereas house dust mites (Der. farinae, Der. pteronyssinus) are the primary allergens for asthma and rhinitis patients in southern and central China. Our findings indicate that inhalant allergens are dominant in South China’s Guangdong area (76.51%), with the highest positivity rates for Der. farinae (93.18%) and Der. pteronyssinus (88.27%), suggesting dust mites as the leading allergens for paediatric respiratory allergies in this region. These findings align with previous research by Chen et al.²³ Notably, the sIgE levels for these two dust mite species were mostly in the levels 3–6, with levels 5–6 accounting for approximately 50% of cases. Literature indicates that sIgE levels typically correlate with the severity of allergic symptoms, where higher sIgE grades correspond to increased likelihood of clinical manifestations.^{24 25} Thus, the high proportion of elevated sIgE levels observed in this study suggests that Der. farinae and Der. pteronyssinus may be key contributors to severe allergic respiratory symptoms in this region.

This study also revealed eggs (14.18%) and milk (11.89%) as the leading causes of food allergies, with sIgE levels mostly at levels 1–2, indicating low-level sensitisation. This is in line with multiple Chinese studies.²⁶,²⁹ Milk is the most common food allergen in infants and young children. However, indiscriminate milk avoidance by caregivers in suspected allergy cases may lead to developmental delays and growth impairment. Component resolved diagnostics, a recently developed method, is more specific and accurate than skin prick tests and food-protein-based sIgE tests. It can identify the exact allergenic protein components in food allergens, enabling targeted elimination of allergenic proteins while maintaining adequate nutritional intake, thereby significantly reducing malnutrition risks.³⁰

Although inhalant allergens are the classic triggers of AR and asthma, growing evidence indicates that food sensitisation and respiratory allergy are immunologically intertwined.³¹ From an immunological cross-reactivity perspective, the respiratory and gastrointestinal tracts share the same mucosal immune system and may interact through the ‘food allergy–gut microbiota–respiratory allergy’ axis.³² The gut microbiota not only influences the development of food allergies but also modulates airway inflammation and IgE-mediated immune responses, leading to impaired lung function.³³,³⁶ Prospective birth-cohort studies show that early-life food sensitisation increases the subsequent risk of AR and asthma during school age.^{37 38} Co-sensitisation to both food and inhalant allergens enhances the production of serum IgE and increases the likelihood and severity of early childhood airway diseases.³⁹,⁴² Additionally, the allergen spectrum varies substantially across geographic regions. Studies conducted in southern China, including Guangdong and Shanghai, have shown that food allergens such as milk, egg and shellfish maintain notable detection rates even among children primarily affected by respiratory allergies.^{29 43} These findings emphasise the necessity of considering both food and inhalant allergens when assessing allergic sensitisation in different populations.

Clinically, AR and asthma are often viewed as interconnected conditions that share common endotypes and risk factors, consistent with the concept of ‘one airway, one disease’. Our study found that patients with AR, asthma and AR-asthma comorbidity show similar sensitisation patterns and share common allergens. These allergens trigger nasal mucosal hypersensitivity reactions, releasing chemical mediators and cytokines into the bloodstream. Through systemic circulation, these inflammatory factors reach the lungs, acting on tracheobronchial smooth muscles to induce spasms and subsequent airway hyper-responsiveness. Therefore, when patients show AR symptoms, active treatment is necessary to lower the risk of developing asthma, alleviate allergic symptoms and enhance the therapeutic and control effects, ultimately improving the quality of life.

Our study systematically confirmed that allergen positivity rates vary with seasons, age and sex. The overall allergen positivity rate was highest in summer, with inhalant allergens peaking in summer and food allergens in spring. This may be due to the subtropical climate promoting mite and cockroach proliferation in summer, while dry, cool weather reduces allergen exposure and alleviates symptoms. In our cohort, food-specific IgE positivity peaked in spring. This pattern is biologically plausible for three reasons. First, the spring pollen season triggers a surge of Th2-skewed immune activation and cross-reactive IgE directed against homologous plant food proteins (pollen-food syndrome), as repeatedly reported in paediatric populations.^{44 45} Second, dietary exposure to fresh legumes, fruits and seafood increases in spring in our region, providing more opportunities for sensitisation. Third, PM2.5 concentrations in our region peak during late winter and early spring. Once these fine particles enter the bloodstream, they can act as carriers that adsorb and concentrate environmental allergens, thereby increasing their immunogenicity and amplifying hypersensitivity reactions, and disrupt respiratory- and intestinal-epithelial tight junctions through oxidative stress, functioning as a Th2-skewing ‘adjuvant’ that promotes allergen sensitisation.⁴⁶ Consistent with these mechanisms, cohort studies from Canada and China have shown a positive association between early-life NO₂ exposure and food allergens.^{47 48} Although direct causal evidence remains limited, this environmental factor may partly contribute to the higher food-IgE positivity we observed in spring.

In terms of age groups, inhalant allergen positivity increased with age, remained high between ages 9 and 14 years, with the peak at 10–11 years. This aligns with findings from Thachera et al in Beijing, China, where inhalant allergen sensitivity peaked at 10–19 years, confirming this age window as a high-risk period for inhalant sensitisation.^{49 50} The heightened risk may stem from increased independent outdoor activities in school-age children, prolonging exposure to inhalant allergens. Conversely, food allergen positivity showed an inverse correlation with age, likely reflecting gastrointestinal immune maturation and oral tolerance development. Thus, in clinics, for children sensitised to milk allergens, especially those ≤6 years old, it is not advisable to blindly restrict such foods. Instead, regular allergen testing is essential.⁵¹ In the gender-based analysis, our results have shown that the positivity rates of inhalant allergens and food allergens were significantly higher in males than females (p<0.001), consistent with previous reports.⁷ Several studies have indicated that AR is more common in males before puberty, whereas it is more common in females after puberty.⁵² This may stem from physiological differences between males and females, yet the exact mechanism requires further study.

Our study also revealed a significant correlation between allergens and routine blood cell differentials and immune markers. Notably, neutrophil percentages and BAS counts showed a strong positive correlation with most allergens, especially dust mites. Although eosinophils are key effector cells in asthma,^{53 54} our study found no significant link between them and 18 allergens. This might be due to the fact that peripheral blood cells are influenced by various bodily factors and can fluctuate over time within the same individual.⁵⁵ Moreover, in asthma, eosinophils migrate from the blood to the lungs to function, so their presence in peripheral blood may not be prominent.⁵⁶ Our analysis of immunological data showed that total immunoglobulin E (tIgE) levels are positively correlated with multiple allergens, which is consistent with recent studies in Beijing, China.^{57 58} Interestingly, immunoglobulin G (IgG) levels were also found to be positively correlated with a variety of allergens, and there were significant differences in IgE and IgG positivity rates for different food allergens. This suggests that combined IgE and IgG testing may enhance the clinical relevance of allergen screening.⁵⁸

This study provides valuable insights but has certain limitations. First, the sIgE levels for allergens were measured using fluorometric enzyme immunoassay, a reliable method, but we only tested for 18 common allergens, so less common allergens might have been overlooked. Second, some children with allergic disease symptoms did not seek timely medical care, leading to incomplete data and possible omissions. Third, the study lacked a healthy control group, so specific outcomes and symptoms could not be compared between affected and healthy children. Some prior studies have shown that socioeconomic status and environmental exposures affect childhood wheeze/asthma/lung function.⁵⁹,⁶² Since this study lacked relevant socioeconomic and environmental covariates, there may be minor residual confounding; however, this does not impact our conclusions. Future research should integrate clinical records with standardised questionnaires and environmental monitoring to better control for potential confounding factors. Despite these flaws, the study has built an allergen profile for Guangdong, China, offering a basis for preventing and treating respiratory allergic diseases there. In our subsequent research phase, we will conduct multicentre studies to expand the scope of allergen detection and perform integrated analyses combining clinical patient data, thereby enhancing evidence-based support for clinical diagnosis and treatment.

In summary, our study corroborates previous findings and advances the field in four key respects: (1) it draws on a substantially larger cohort; (2) it broadens the clinical scope from isolated AR to three phenotypes—AR, asthma and their coexistence; (3) it concurrently analyses sensitisation to both food and inhalant allergens and (4) it links specific IgE profiles to objective measures of lung function and airway inflammation. Together, these contributions provide a more integrated view of paediatric allergic disease and furnish a data-driven foundation for refining phenotype-specific prevention and treatment strategies.

Conclusions

Our study has unveiled that children with AR and/or asthma in Guangdong frequently exhibit positive reactions to two allergens. Among the inhalant allergens, Der. farinae and Der. pteronyssinus were particularly prevalent, followed by ingested allergens such as whole egg and milk. Fungal and weed pollen allergens also exhibited significant positivity. The rates of allergen positivity varied with seasonal fluctuations, age and gender. Furthermore, the study observed correlations between routine blood parameters, immune markers and specific allergens, as well as associations among allergens, routine blood parameters, immune markers and pulmonary function. These findings emphasise the necessity of incorporating gender, age, seasonal patterns, geographical factors and haematological/immunological profiles into clinical decision-making for paediatric allergic respiratory diseases. They provide critical epidemiological evidence for establishing a paediatric allergen exposure map and precision prevention frameworks in China’s subtropical regions.

Data availability statement

Data are available upon reasonable request.