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Breastfeeding, genetic susceptibility, and the risk of asthma and allergic diseases in children and adolescents: a retrospective national population-based cohort study

BMC Public Health volume 24, Article number: 3056 (2024) Cite this article

Abstract

Background

Asthma and allergic diseases (such as allergic rhinitis) are multifactorial chronic respiratory diseases, and have many common pathogenic mechanisms. This study aimed to assess the joint effects of breastfeeding and genetic susceptibility on asthma, allergic disease in children and adolescents and sought to examine whether the effect of breastfeeding was consistent under distinct levels of genetic risk.

Methods

A total of 351,931 UK Biobank participants were analyzed. Firstly, Cox proportional hazards model was used to evaluate the relation between breastfeeding and asthma, allergic disease and their comorbidity. Next, we incorporated the polygenic risk score as an additional covariate into the model. Then, we explored the role of breastfeeding at each stage of asthma and allergic disease through a multi-state model. Meanwhile, several sensitivity analyses were conducted to evaluate the robustness of our results. Finally, we calculated the attributable protection and population attributable protection of breastfeeding.

Results

Breastfeeding was related to a reduced risk of occurring asthma (adjusted hazard ratio [HR] = 0.89, 95% confidence interval [CI] 0.86 ~ 0.93), allergic disease (HR = 0.89, 95%CI 0.87 ~ 0.91) and comorbidity (HR = 0.89, 95%CI 0.83 ~ 0.94). The effect of breastfeeding was almost unchanged after considering PRS and did not substantially differ across distinct genetic risk levels. Breastfeeding showed a stronger risk-decreased impact on individuals who developed from allergic rhinitis to comorbidity (HR = 0.83, 95%CI 0.73 ~ 0.93). Further, the influence of breastfeeding was robust against covariates considered and the confounding influence of adolescent smoking. Finally, due to breastfeeding, 12.0%, 13.0% or 13.0% of the exposed population would not suffer from asthma, allergic diseases and the comorbidity, while 7.1%, 7.6% or 7.6% of the general population would not suffer from these diseases.

Conclusions

This study provided supportive evidence for the risk-reduced effect of breastfeeding on asthma, allergic diseases, and the comorbidity in children and adolescents, and further revealed that such an influence was consistent across distinct genetic risk levels.

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Introduction

Asthma [1] and allergic diseases (such as allergic rhinitis [2]) are multifactorial chronic respiratory diseases, and have many common pathogenesis. These two types of diseases affect all age groups. In the past few years, their prevalence rate has continued to increase in many countries (especially among children) [2, 3], which has led to serious global health problems, including impaired quality of life, school or work performance, and significant economic impact [4]. The causes of asthma and allergic diseases include genetic and environmental factors, and it is generally believed that the early living environment (such as nutrition) has a considerable influence on the risk of developing asthma and allergies [5].

Nutrition in the very early years of life (such as neonatal period) can be provided through breastfeeding or formula milk, followed by complementary foods, but the immunomodulatory components of breast milk, such as maternal antibodies, are not available in formula milk [6]. Many studies have demonstrated that breastfeeding can significantly prevent and reduce the risk of asthma and allergic diseases in children [7,8,9]; therefore, exclusive breastfeeding is recommended to last at least four to six months [10]. Unfortunately, not all studies have confirmed the preventive and protective effects of breastfeeding on asthma and allergic diseases [11, 12].

On the other hand, genetic susceptibility also plays an important role in the development of asthma and allergic diseases [13], with the heritability estimated to be 25 ~ 80% for asthma [14] and up to 90% for allergic rhinitis [15]. Recently, large-scale genome-wide association studies (GWASs) discovered a large number of genetic variations related to the risk of asthma and allergic diseases [14, 16], and found that there was a high degree of genetic overlap among these diseases [13, 17].

However, thus far, few studies have investigated the joint effects of breastfeeding and genetic susceptibility on asthma and allergic diseases, or examined whether the effect of breastfeeding may be affected by genetic susceptibility. In addition, previous studies that reported the protective association of breastfeeding only focused on allergic response in early childhood (for example, before 6 years old [18] or 4 ~ 12 years old [19]), and very limited studies explored its long-term effect on asthma and allergic diseases among older children. Thereby, the role of breastfeeding throughout adolescence needs further investigation [20].

To handle the above problems, in the present study we sought to evaluate the association between breastfeeding and the onset of asthma and allergic diseases up to the age of 18 years using the UK Biobank cohort data [21]. In particular, we studied the joint effects of breastfeeding and genetic susceptibility on asthma and allergic diseases, and further evaluated whether the effect of breastfeeding are consistent at different levels of genetic susceptibility.

Methods and materials

UK Biobank cohort

Our research is a retrospective national population-based cohort study that relies on the UK Biobank, which collected an unprecedented amount of biological and medical data resource on more than 500,000 participants in 22 centers across the UK aged 40 ~ 69 years since 2006 [21]. Most of the participants were British whites, who had been to the center at baseline, but some visited it more than three times during the follow-up period. In our analysis, we only considered participants of white ancestry. The UK Biobank has approval from the North West Multi-Center Research Ethics Committee (MREC) as a Research Tissue Bank (RTB) approval, meaning other researchers do not require separate ethical clearance and can operate under this approval.

Ascertainment of breastfeeding, asthma, and allergic diseases

Breastfeeding was defined as a binary variable (yes or no) by the answer to the following question: “were you breastfeed when you were a baby?” We chose individuals who had a physician-diagnosed asthma and hay fever, allergic rhinitis, or eczema as cases, which were defined by the question: “has your doctor ever told you that you have had any of the following conditions?” Because hay fever, allergic rhinitis and eczema are classified into one category, we considered them together by following a previous study [22] and referred to as HAE.

Breastfeeding, asthma and allergic diseases were determined according to the baseline information, and if the baseline information was missing, the follow-up data were used instead. We also analyzed the comorbidity of asthma and HAE, and referred to it as AHAE. We ensured each selected case had the onset age and only focused on children/adolescent cases (age at onset ≤ 18 years old) as the protective role of breastfeeding appeared difficult to persist into adulthood [23]. Therefore, individuals with age at onset larger than 18 were excluded. Finally, 351,931 participants were kept. The flow diagram of data processing is displayed in Fig. 1.

Fig. 1
figure 1

Flow diagram of data processing and statistical analysis for the present study using the UK Biobank cohort data. PRS, polygenic risk score; HAE, hay fever, allergic rhinitis, and eczema; AHAE, the comorbidity of asthma and HAE. AP, attributable protection; PAP, population attributable protection

Full size image

Covariate selection

According to our previous work [24], we included birthweight, maternal smoking during pregnancy, smoking/smokers in household, average total household income before tax, diet score and gender as potential covariates, which either conceptually had an impact on or showed statistically significant connection with our analyzed diseases [25]. The diet score was calculated based on baseline self-reported dietary data (such as intake of fruits, vegetables, meat, etc.). We also included the top ten genetic principal components (GPC) in our analysis to explain possible relatedness among selected participants [26]. We imputed missing values of covariates by multivariate imputation by chained equations (MICE) [27], but ruled out participants with missing values in breastfeeding, asthma, HAE or AHAE.

Calculation of polygenic risk score

Considering the pervasive polygenic and multi-local nature of disease associations and the relatively small influence of a single genetic variant, PRS has been proposed to evaluate the cumulative impact of multiple risk-related single nucleotide polymorphisms (SNPs) [28, 29]. For each analyzed disease, we calculated its PRS with genetic effect sizes available from summary statistics via PRS-CS [30], with the 1000 Genomes Project European samples (n = 503) as the external linkage disequilibrium (LD) reference panel. We obtained the summary statistics of white ancestors from the hitherto largest genome-wide association studies (GWASs) (Table S1). According to previous studies [31,32,33,34], we performed strict quality control for these summary statistics data.

Statistical analysis

Cox proportional hazards model

We applied the onset age (0 ~ 18 years old) to represent the occurrence time of asthma, HAE or AHAE [35], and set the occurrence time of these non-cases to 18 years old. Cox proportional hazards model was applied to assess the relationship between breastfeeding and asthma (HAE or AHAE) while adjusting for the covariates mentioned before. According to Schoenfeld’s residual method [36], we did not find any evidence that violated the proportional hazards hypothesis (P > 0.05).

We next incorporated standardized PRS into the model as another covariate. PRS was further divided into deciles and tertiles to explore how much the risk of disease changed as the genetic risk increased and to examine whether the breastfeeding effect was different across distinct genetic risk levels. Hazard ratio (HR) and its 95% confidence interval (CI) were reported.

We also conducted stratified analyses based on different levels of covariates. For instance, we divided age at onset into three groups (0 ~ 6 years, 7 ~ 12 years, and 13 ~ 18 years) following previous studies [18, 24], and classified birthweight as low (< 2.5 kg), normal (2.5–4.0 kg), and high (≥ 4.0 kg) levels according to pediatric and existing studies [37,38,39].

Sensitivity analyses

We conducted two sensitivity analyses to evaluate the robustness of our results. First, because it was uncertain whether current household smoking status, income, or diet could be substituted for exposure before the age of 18, we conducted a similar analysis without considering smoking/smokers in household, average total household income before tax and diet score. Second, we also adjusted for adolescent smoking [40, 41] because smoking can cause asthma and aggravate the symptoms of allergic rhinitis. Because adolescent smoking was not directly available in the UK Biobank, we generated a new variable (yes or no) via the age at smoking and age at quitting before the age of 18.

Multi-state model

Here, we implemented the multi-state model [42, 43] to assess the role of breastfeeding in each stage of disease progression from baseline to a disease (asthma or HAE) and to comorbidity (AHAE) or from baseline to comorbidity. The multi-state model provides a unique advantage by treating various diseases as different transitional states, and can investigate the influence of exposure on different stages of disease progress in the presence of competitive risks. This analysis was conducted in a similar way via Cox proportional hazards model with the above six variables as covariates.

Attributable protection and population attributable protection

Finally, in order to further quantify the risk-reduced influence of breastfeeding on asthma and allergic diseases, attributable protection (AP%) and population attributable protection (PAP%) were calculated to estimate the percentage of cases reduction [44]. Briefly, AP%=(1-HR)/HR and PAP%=Pe(1-HR)/[Pe(1-HR) + 1], where Pe was the breastfeeding rate, which varied across the three diseases’ data.

Results

Description of the used dataset

We reserved 11,988 asthma cases and 308,831 non-asthma participants, 35,281 HAE cases and 264,297 non-HAE participants, and 5,332 AHAE cases and 242,548 non-AHAE participants. The cumulative incidences of the three types of diseases increasing as age are shown in Figure S1. Summary information of involved variables is shown in Table S2. In the asthma, HAE and AHAE datasets, the breastfeeding rates were 71.4%, 71.3% and 71.7%, respectively, and the breastfeeding rates of non-case participants were generally higher than those of cases.

Estimated effect of breastfeeding on Asthma, HAE, and AHAE

We found that breastfed children had a lower risk of developing asthma compared to those not breastfed (the crude HR = 0.91, 95%CI 0.88 ~ 0.95), the effect was almost unchanged after taking covariates into account (the adjusted HR = 0.89, 95%CI 0.86 ~ 0.93) (Table 1). The significant association of breastfeeding was also consistently observed for HAE (the crude HR = 0.90, 95%CI 0.88 ~ 0.92) and AHAE (the crude HR = 0.90, 95%CI 0.85 ~ 0.96), with the adjusted HR = 0.89 (95%CI 0.87 ~ 0.91) for HAE and 0.89 (95%CI 0.83 ~ 0.94) for AHAE when covariates were considered.

The stratified analysis showed that the effects of breastfeeding on asthma, HAE, and AHAE were essentially similar across different levels of covariates (Table S3). When stratified by age at onset, we discovered the association of breastfeeding with HAE (Pheterogeneity=0.170) or AHAE (Pheterogeneity=0.799) persisted across distinct onset age groups (Table S4); however, breastfeeding exhibited the strongest effect on asthma adolescents aged 13 ~ 18 years (Pheterogeneity=0.004).

The adjustment of adolescent smoking did not significantly change the influence of breastfeeding on asthma, HAE, or AHAE (Table S5). The estimated effects were also nearly consistent after excluding smoking/smokers in household, diet score and average total household income before tax (Table S5).

Table 1 HR and 95%CI for the association of breastfeeding with the risk of Asthma, HAE, and AHAE
Full size table

Estimated effect of breastfeeding on Asthma, HAE, and AHAE when taking PRS into account

The effects of breastfeeding on asthma, HAE, and AHAE were almost unchanged when PRS was included to explain the impact of genetic risk (Table 1). For example, the HRs of breastfeeding were 0.89 (95%CI 0.86 ~ 0.93) for asthma, 0.89 (95%CI 0.87 ~ 0.91) for HAE, and 0.89 (95%CI 0.84 ~ 0.94) for AHAE, respectively. In terms of the stratified analysis by PRS, there was no significant difference in the association of breastfeeding across various genetic risk levels (Fig. 2).

Fig. 2
figure 2

Forest plot of effects of breastfeeding on Asthma, HAE and AHAE in children under 18 years old when stratified by PRS. HR, hazard ratio; CI, confidence interval; HAE, hay fever, allergic rhinitis, and eczema; AHAE, the comorbidity of asthma and HAE

Full size image

We observed that per SD increase in PRS had a significant influence on the risk of asthma (HR = 1.52, 95%CI 1.49 ~ 1.55), HAE (HR = 1.08, 95%CI 1.07 ~ 1.09) and AHAE (HR = 1.39, 95%CI 1.35 ~ 1.43), and there existed a progressively elevated impact on the risk of encountering asthma, HAE, or AHAE as PRS increased (Figure S2). Participants with high genetic risk (top tertile) showed a 151% (95%CI 139 ~ 163%), 17% (95%CI 14 ~ 20%), and 106% (95%CI 93 ~ 121%) higher risk of developing asthma, HAE or AHAE compared to those with low genetic risk (bottom tertile), respectively. These effects did not significantly change after additional adjustment for breastfeeding (Table S6).

Estimated effect of breastfeeding in each stage of AHAE progression in the multi-state model

The results of the path analysis from baseline to one disease or two diseases are shown in Fig. 3. For the transition from baseline to one disease, the impact of breastfeeding on HAE was comparable to that for asthma shown above. For the transition from one disease to AHAE, participants with asthma seemed more likely (15.0%) to further develop AHAE compared with the transition from allergic diseases to AHAE (3.7%). However, the influence of breastfeeding seemed slightly more evident for the path from allergic diseases to AHAE (HR = 0.83, 95%CI 0.73 ~ 0.93) relative to the path from asthma to AHAE (HR = 0.90, 95%CI 0.81 ~ 1.00).

Fig. 3
figure 3

Analysis path from baseline to the occurrence of one disease and then to the existence of two diseases. HR, hazard ratio; CI, confidence interval; HAE, hay fever, allergic rhinitis, and eczema; AHAE, the comorbidity of asthma and HAE

Full size image

Population attributable protection of incident Asthma, HAE and AHAE

In terms of the breastfeeding rates and the estimated HRs, we showed that AP% of asthma, HAE and AHAE was 12.0%, 13.0% and 13.0%, while PAP% of asthma, HAE and AHAE was 7.1%, 7.6% and 7.6%. Taking asthma for example, the incidence of asthma was expected to reduce by 12.0% in the breastfed population and 7.1% in the general population if they were breastfed.

We then calculated AP% and PAP% after stratifying by PRS, and found a similar risk-reduced influence of breastfeeding on participants across various levels of genetic predisposition in the HAE population. However, for asthma and AHAE, breastfeeding showed more evident influence on those with high PRS (Table S7). For example, breastfeeding substantially reduced AHAE from 13.0% for participants with the highest PRS to 6.4% for those with the lowest PRS.

Discussion

Summary of our results

In this study, we have demonstrated that breastfeeding could lead to a decreased risk of suffering from asthma, hay fever, allergic rhinitis, and eczema in children and adolescents, as well as the comorbidity of these diseases. In terms of the transition from a disease to the comorbidity, we discovered that participants with asthma were more likely to progress to comorbidity and breastfeeding had a stronger risk-reduced effect on individuals who developed from allergic rhinitis to comorbidity. Further, the effects of breastfeeding on asthma and allergic diseases were still significant after PRS was included to explain the effect of genetic risk and remained nearly consistent across distinct genetic risk levels.

Comparison with previous studies

Our work supported and complemented the previous research in three aspects. First, some previous studies have proved the relationship between breastfeeding and asthma as well as between breastfeeding and hay fever, allergic rhinitis, or eczema [18, 45]; however, other population-based studies generated inconsistent conclusions. For example, it was discovered that breastfeeding (any or exclusive) showed an insignificant effect on asthma and allergic disease in the IoW cohort [5]. Relying on the large-scale UK Biobank cohort, we offered substantial evidence supporting the association of breastfeeding with asthma and hay fever, allergic rhinitis, and eczema.

Second, some studies on food allergy showed that it was important to consider individual genetic variation when evaluating the relation between breastfeeding and food allergy [46]. In this spirit, we included PRS to explain the effect of genetic risk, and discovered that the effect of breastfeeding did not change much at various genetic risk levels.

Third, contrary to existing studies which demonstrated a possible interaction between breastfeeding and genetic risk [47, 48], we found that the associations between breastfeeding and asthma, hay fever, allergic rhinitis, and eczema, and the relationship between breastfeeding and the comorbidity of these diseases were very similar across all dimensions of genetic risk, which indicated the pervasive benefit of breastfeeding for the whole population under 18 years old.

Advantages of this work

Compared with the previous work, our research has four main advantages. First, the data we analyzed were obtained from the UK Biobank cohort and had a much larger sample size than existing studies; therefore, the sampling error has little influence on the results [49, 50]. Second, we further considered the comorbidity of asthma and allergic diseases, which was very common in practice [51] but rarely discussed before. Third, for the first time, we combined breastfeeding and PRS together to evaluate their joint influences. Fourth, the multi-state model was conducted, which allowed us to explore the effects of breastfeeding on the different stages of the full disease process.

Limitations of this work

There are also some limitations that need to be highlighted. First, due to potential recall bias, breastfeeding, asthma and allergic diseases might be wrongly classified [52, 53]. Meanwhile, we did not consider other important confounders such as length and exclusivity of breastfeeding, family history, maternal gestational age, and maternal/paternal educational level because they cannot be accurately available in the UK Biobank cohort [54, 55]. In addition, we had to employ some adult variables (smoking/smokers in household and average total household income before tax) as the proxies of covariates which needed to adjust for because the relevant information was unavailable for children and adolescents in the UK Biobank cohort. However, through some additional analyses, we found that doing this seemed not to have a substantial influence on our findings. Nevertheless, we cannot rule out the possibility that those unmeasured covariates likely biased our results.

Second, there might exist a reverse relationship [56]; that is to say, early symptoms of asthma and allergic diseases had existed during breastfeeding, which prompted the mothers to continue breastfeeding. This may weaken the impact of breastfeeding and even lead to the spurious conclusion that breastfeeding will increase the risk of asthma, hay fever, allergic rhinitis, or eczema.

Third, the UK Biobank consists mainly of Caucasians from developed countries, and there are large differences in breastfeeding rates across various national races [57], which likely limits the generalization of our findings to populations with other genetic backgrounds and relatively low socio-economic levels.

Public health implications of our findings

Although the risks of not breastfeeding have been widely documented, breastfeeding initiation rates remain relatively low in many high-income countries, particularly among women from low-income regions [58]. The decision of breastfeeding is influenced by multiple and complex factors at the individual, family, health system and societal levels [59]. In view of the health benefits of breastfeeding observed in current research, our findings are of great significance for strengthening breastfeeding suggestions and improving the health status of future generations [46].

In addition, our results offered a deep understanding of the impact of breastfeeding on allergic diseases, regardless of the background of individual genetic variation. Our results also indicate that there is an opportunity to prevent asthma and allergic diseases in children from the beginning (as early as lactation), and to reduce the risk of developing these diseases in the future.

Conclusions

We provided supportive evidence for the significant association of breastfeeding with the reduced risk of asthma, allergic diseases, and comorbidities in children and adolescents less than 18 years of age, and further revealed that this influence was not affected by various genetic susceptibility levels. These findings were helpful in encouraging mothers to initiate and prolong breastfeeding.

Data availability

This study used the UK Biobank resource with the application ID 88159. Researchers can access to the UK Biobank dataset by applying to the UK Biobank official website (https://www.ukbiobank.ac.uk/).

Abbreviations

PRS:

Polygenic Risk Score

HR:

Hazard Ratio

CI:

Confidence Interval

GWASs:

Genome-Wide Association Studies

MREC:

Multi-Center Research Ethics Committee

RTB:

Research Tissue Bank

HAE:

Hay fever, Allergic rhinitis, and Eczema

AHAE:

Comorbidity of Asthma and Hay fever, Allergic rhinitis, and Eczema

GPC:

Genetic Principal Components

MICE:

Multivariate Imputation by Chained Equations

SNPs:

Single-Nucleotide Polymorphisms

AP%:

Attributable Protection

PAP%:

Population Attributable Protection

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Acknowledgements

This study was also based on the UK Biobank resource under application number 88159. The UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government, and the Northwest Regional Development Agency. It has also had funding from the Welsh Assembly Government, British Heart Foundation and Diabetes UK. The data analyses in the present study were carried out with the high-performance computing cluster that was supported by the special central finance project of local universities for Xuzhou Medical University. We thank the Editor, Associate Editor, and three anonymous reviewers for their constructive comments which substantially improved our manuscript.

Funding

The research of Ping Zeng was supported in part by the National Natural Science Foundation of China (82173630), the Natural Science Foundation of Jiangsu Province of China (BK20241952), the QingLan Research Project of Jiangsu Province for Young and Middle-aged Academic Leaders, and the Six-Talent Peaks Project in Jiangsu Province of China (WSN-087).

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Author notes

  1. Wenyan Hou and Fengjun Guan are co-first authors.

Authors and Affiliations

  1. Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China

    Wenyan Hou, Wenying Chen, Jike Qi, Shuiping Huang & Ping Zeng

  2. Department of Pediatrics, Affiliated Hospital of Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China

    Fengjun Guan

  3. Jiangsu Engineering Research Center of Biological Data Mining and Healthcare Transformation, Xuzhou Medical University, Xuzhou, Jiangsu, 221004, China

    Shuiping Huang & Ping Zeng

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Contributions

PZ conceived the idea for the study. PZ obtained the data. PZ, FG and WH cleared up the datasets and performed the data analyses. PZ, SH, JQ, WC and WH interpreted the results of the data analyses. PZ and WH wrote the manuscript with the participation of other authors.

Corresponding authors

Correspondence to Shuiping Huang or Ping Zeng.

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Ethics approval and consent to participate

The UK Biobank had approval from the North West Multi-Centre Research Ethics Committee (MREC) as a Research Tissue Bank (RTB) approval. All participants provided written informed consent before enrolment in the study, which was conducted in accordance with the Declaration of Helsinki. This approval means that researchers do not require separate ethical clearance and can operate under the RTB approval.

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Not applicable.

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The authors declare no competing interests.

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Hou, W., Guan, F., Chen, W. et al. Breastfeeding, genetic susceptibility, and the risk of asthma and allergic diseases in children and adolescents: a retrospective national population-based cohort study. BMC Public Health 24, 3056 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12889-024-20501-0

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BMC Public Health

ISSN: 1471-2458

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