The association between a genetic risk score for allergy and the risk of developing allergies in childhood-Results of the WHISTLER cohort

Allergic disease trajectories up to adolescence: Characteristics, early-life, and genetic determinants

BACKGROUND

Allergic diseases often develop jointly during early childhood but differ in timing of onset, remission, and progression. Their disease course over time is often difficult to predict and determinants are not well understood.

OBJECTIVES

We aimed to identify trajectories of allergic diseases up to adolescence and to investigate their association with early-life and genetic determinants and clinical characteristics.

METHODS

Longitudinal k-means clustering was used to derive trajectories of allergic diseases (asthma, atopic dermatitis, and rhinitis) in two German birth cohorts (GINIplus/LISA). Associations with early-life determinants, polygenic risk scores, food and aeroallergen sensitization, and lung function were estimated by multinomial models. The results were replicated in the independent Swedish BAMSE cohort.

RESULTS

Seven allergic disease trajectories were identified: "Intermittently allergic," "rhinitis," "early-resolving dermatitis," "mid-persisting dermatitis," "multimorbid," "persisting dermatitis plus rhinitis," and "early-transient asthma." Family history of allergies was more prevalent in all allergic disease trajectories compared the non-allergic controls with stronger effect sizes for clusters comprising more than one allergic disease (e.g., RRR = 5.0, 95% CI = [3.1-8.0] in the multimorbid versus 1.8 [1.4-2.4] in the mild intermittently allergic cluster). Specific polygenic risk scores for single allergic diseases were significantly associated with their relevant trajectories. The derived trajectories and their association with genetic effects and clinical characteristics showed similar results in BAMSE.

CONCLUSION

Seven robust allergic clusters were identified and showed associations with early life and genetic factors as well as clinical characteristics.

Birth cohort studies using symptom diaries for assessing respiratory diseases–a scoping review

Background

Respiratory infections are the most frequent health problem in childhood leading to morbidity and socioeconomic burden. Studying symptoms of respiratory infections in home based settings requires dedicated prospective cohort studies using diaries. However, no information is available on which birth cohort studies using symptom diary data. A review of birth cohort studies with available symptom diary data, follow-up data, and bio samples is needed to support research collaborations and create potential synergies.

Methods

We conducted a scoping review of birth cohort studies using diaries for the collection of respiratory symptoms. The scoping review was conducted in accordance with the PRISMA Extension. We searched the electronic databases PubMed, Embase, Web of science and CINAHL (last search November 2020) resulting in 5872 records (based on title and abstract screening) eligible for further screening.

Results

We examined 735 records as full text articles and finally included 57 according to predefined inclusion criteria. We identified 22 birth cohort studies that collect(ed) data on respiratory symptoms using a symptom diary starting at birth. Numbers of participants ranged from 129 to 8677. Eight studies collected symptom diary information only for the first year of life, nine for the first two years or less and six between three and six years. Most of the cohorts collected biosamples (n = 18) and information on environmental exposures (n = 19).

Conclusion

Information on respiratory symptoms with daily resolution was collected in several birth cohorts, often including related biosamples, and these data and samples can be used to study full spectrum of infections, particularly including those which did not require medical treatment.

Association of a four-gene model with allergic diseases: Two-year follow-up of a birth cohort study

Background

Our previous study has developed a four‐gene model involving IL13 rs20541, IL4 rs2243250, ADRB2 rs1042713, and FCER1B rs569108 associated with asthma and atopy in Chinese Han children. However, whether the gene model is associated with allergies in early life has yet to be determined. This study aimed to apply the gene model in a birth cohort to investigate its associations with the development of allergic diseases in Chinese Han toddlers.

Methods

Five hundred and ninety‐seven children from a birth cohort completing 2‐year follow‐up were included. Epidemiologic information and cord blood were collected. Children were genotyped for the above polymorphisms and divided into high or low genetic risk groups based on the genotypes. Subjects were followed at 6, 12, and 24 months, with information on allergic diseases collected via standard questionnaires and assessed by specialists.

Results

Two hundred and eighty‐four children were divided into a high‐risk group and 313 into a low‐risk group. Between the two groups, a significant difference was only found in delivery mode among all the subject characteristics (p = .025). After stratification for delivery mode, children at high risk were more likely to develop eczema (relative risk [RR] = 1.46, p = .040) over 2 years of follow‐up compared with those at low risk. No significant associations were found between genetic risk and food allergy, wheezing and allergic rhinitis (p > .05).

Conclusion

The gene model was significantly associated with the development of eczema in Chinese Han toddlers. Long‐term follow‐up along with functional and replication studies on the gene model are still needed in future.

Vegetable dietary pattern may protect mild and persistent allergic rhinitis phenotype depending on genetic risk in school children

BACKGROUND

The effect of diet on allergic rhinitis (AR), its severity in children, and whether it modifies AR depending on genetic susceptibility are unknown. We investigated the association between dietary patterns and AR in school children and the influence of diet on AR according to a genetic risk score (GRS).

METHODS

Totally, 435 7-year-old school children were recruited from the Panel Study on Korean Children. We used dietary patterns (vegetable, sugar, and meat) and dietary inflammatory index (DII) as dietary parameters. AR and its severity were defined by questionnaires about treatment in the previous 12 months and the Allergic Rhinitis and its Impact on Asthma (ARIA) guideline, respectively. A GRS was calculated using 6 single nucleotide polymorphisms for allergic diseases.

RESULTS

A vegetable diet containing a lot of anti-inflammatory nutrients and higher vitamin D level in blood were negatively correlated, while DII was positively correlated with triglyceride level and triglyceride/HDL cholesterol. Vegetable diet (aOR, 95% CI = 0.73, 0.58-0.94) and DII (1.13, 1.01-1.28) were associated with AR risk. In particular, a high-vegetable diet resulted in a lower risk of mild and persistent AR (aOR, 95% CI = 0.24, 0.10-0.56) while a high DII represented a higher risk (2.33, 1.06-5.10). The protective effect of vegetable diet on AR appeared only among children with a lower GRS (adjusted P = .018).

CONCLUSIONS

A vegetable dietary pattern characterized by high intake of anti-inflammatory nutrients and higher vitamin D level in blood might be associated with a lower risk of mild and persistent AR. This beneficial effect is modified by a genetic factor.

Systems biology and big data in asthma and allergy: recent discoveries and emerging challenges

Asthma is a common condition caused by immune and respiratory dysfunction, and it is often linked to allergy. A systems perspective may prove helpful in unravelling the complexity of asthma and allergy. Our aim is to give an overview of systems biology approaches used in allergy and asthma research. Specifically, we describe recent "omic"-level findings, and examine how these findings have been systematically integrated to generate further insight.Current research suggests that allergy is driven by genetic and epigenetic factors, in concert with environmental factors such as microbiome and diet, leading to early-life disturbance in immunological development and disruption of balance within key immuno-inflammatory pathways. Variation in inherited susceptibility and exposures causes heterogeneity in manifestations of asthma and other allergic diseases. Machine learning approaches are being used to explore this heterogeneity, and to probe the pathophysiological patterns or "endotypes" that correlate with subphenotypes of asthma and allergy. Mathematical models are being built based on genomic, transcriptomic and proteomic data to predict or discriminate disease phenotypes, and to describe the biomolecular networks behind asthma.The use of systems biology in allergy and asthma research is rapidly growing, and has so far yielded fruitful results. However, the scale and multidisciplinary nature of this research means that it is accompanied by new challenges. Ultimately, it is hoped that systems medicine, with its integration of omics data into clinical practice, can pave the way to more precise, personalised and effective management of asthma.

Parental and child factors associated with inhalant and food allergy in a population-based prospective cohort study: the Generation R Study

The prevalence of allergic diseases in children is markedly increasing to epidemic proportions. The aim of this study is to describe the presence and examine associated parental and child characteristics of allergic sensitization and physician-diagnosed allergy in Dutch children at age 10 years. This study among 5471 children was performed in a population-based prospective cohort from fetal life onwards. Allergic sensitization was measured by skin prick tests. Physician-diagnosed allergy and parental and child characteristics were collected by questionnaires. In children aged 10 years, inhalant and food allergic sensitization was present in 32.2% and 7.1%, and physician-diagnosed inhalant and food allergy in 12.4% and 2.3%. Maternal and paternal history of allergy, eczema or asthma was associated with increased risks of physician-diagnosed inhalant allergy (aOR (95% CI) 1.44 (1.23-1.70) and 1.59 (1.30-1.94), respectively), but not with food allergy. Asthma and eczema ever at age 10 years were associated with increased risks of physician-diagnosed inhalant allergy (4.60 (3.55-5.96) and 2.42 (1.94-3.03), respectively). Eczema ever at age 10 years was associated with an increased risk of physician-diagnosed food allergy (5.78, 3.04-9.52), with the highest risk of cashew (7.36, 3.20-16.94) and peanut (5.58, 3.08-10.10) food allergy.Conclusions: We found strong effects of parental history of allergy, eczema or asthma on the presence of physician-diagnosed inhalant allergy in children at age 10 years. Eczema ever at age 10 years was a strong risk factor for the development of physician-diagnosed inhalant and food allergy. What is Known: • The prevalence of allergic diseases in children has markedly increased. • Early-life influences are critically important in the development of allergic diseases. What is New: • Maternal and paternal history of allergy, eczema or asthma is associated with increased risks of physician-diagnosed inhalant allergy but not with food allergy. • Eczema ever at age 10 years is associated with an increased risk of physician-diagnosed food allergy, with the highest risk for cashew and peanut food allergy.

Missing single nucleotide polymorphisms in Genetic Risk Scores: A simulation study

Using a genetic risk score (GRS) to predict a phenotype in a target sample can be complicated by missing data on the single nucleotide polymorphisms (SNPs) that comprise the GRS. This is usually addressed by imputation, omission of the SNPs or by replacing the missing SNPs with proxy SNPs. To assess the impact of the omission and proxy approaches on effect size estimation and predictive ability of weighted and unweighted GRS with small numbers of SNPs, we simulated a dichotomous phenotype conditional on real genotype data. We considered scenarios in which the proportion of missing SNPs ranged from 20-70%. We assessed the impact of omitting or replacing missing SNPs on the association between the GRS and phenotype, the corresponding statistical power and the area under the receiver operating curve. Omission resulted in a larger bias towards the null value of the effect size, a smaller predictive ability and greater loss of statistical power than proxy approaches. The predictive ability of a weighted GRS that includes SNPs with large weights depends of the availability of these large-weight SNPs.