Cohort Profile: Swedish Twin Study on Prediction and Prevention of Asthma (STOPPA)

Explainable artificial intelligence for cough-related quality of life impairment prediction in asthmatic patients

Explainable Artificial Intelligence (XAI) is becoming a disruptive trend in healthcare, allowing for transparency and interpretability of autonomous decision-making. In this study, we present an innovative application of a rule-based classification model to identify the main causes of chronic cough-related quality of life (QoL) impairment in a cohort of asthmatic patients. The proposed approach first involves the design of a suitable symptoms questionnaire and the subsequent analyses via XAI. Specifically, feature ranking, derived from statistically validated decision rules, helped in automatically identifying the main factors influencing an impaired QoL: pharynx/larynx and upper airways when asthma is under control, and asthma itself and digestive trait when asthma is not controlled. Moreover, the obtained if-then rules identified specific thresholds on the symptoms associated to the impaired QoL. These results, by finding priorities among symptoms, may prove helpful in supporting physicians in the choice of the most adequate diagnostic/therapeutic plan.

Preterm birth reduces the risk of IgE sensitization up to early adulthood: A population-based birth cohort study

BACKGROUND

Immunoglobulin E (IgE) sensitization is associated with asthma and allergic diseases. Gestational age influences early immune system development, thereby potentially affecting the process of tolerance induction to allergens.

OBJECTIVE

To study IgE sensitization to common allergens by gestational age from childhood up to early adulthood.

METHODS

Population-based birth cohort, data from the Swedish BAMSE study were used. Allergen-specific IgE antibodies to a mix of common food (fx5) and inhalant (Phadiatop) allergens were analysed at 4, 8, 16 and 24 years. Sensitization was defined as allergen-specific IgE ≥0.35 kU_A /L to fx5 and/or Phadiatop at each time point. Using logistic regression and generalized estimated equations, adjusted odds ratios (aORs) for sensitization in relation to gestational age were calculated. Replication was sought within the Swedish twin study STOPPA.

RESULTS

In BAMSE, 3522 participants were screened for IgE antibodies during follow-up; of these, 197 (5.6%) were born preterm (<37 gestational weeks) and 330 (9.4%) post-term (≥42 weeks). Preterm birth reduced the risk of sensitization to common food and/or inhalant allergens up to early adulthood by 29% (overall aOR = 0.71; 95% CI: 0.52-0.98), and to food allergens specifically by 40% (overall aOR = 0.60; 95% CI: 0.38-0.93). No relation was found between post-term birth and IgE sensitization at any time point. Replication analyses in STOPPA (N = 675) showed similar risk estimates for sensitization to food and/or inhalant allergens (aOR = 0.72; 95% CI: 0.42-1.21), which resulted in a combined meta-analysis aOR = 0.71 (95% CI: 0.54-0.94).

CONCLUSIONS

Our study suggests an inverse association between preterm birth and long-term IgE sensitization.

A System Pharmacology Multi-Omics Approach toward Uncontrolled Pediatric Asthma

There is a clinical need to identify children with poor asthma control as early as possible, to optimize treatment and/or to find therapeutic alternatives. Here, we present the “Systems Pharmacology Approach to Uncontrolled Pediatric Asthma” (SysPharmPediA) study, which aims to establish a pediatric cohort of moderate-to-severe uncontrolled and controlled patients with asthma, to investigate pathophysiological mechanisms underlying uncontrolled moderate-to-severe asthma in children on maintenance treatment, using a multi-omics systems medicine approach. In this multicenter observational case–control study, moderate-to-severe asthmatic children (age; 6–17 years) were included from four European countries (Netherlands, Germany, Spain, and Slovenia). Subjects were classified based on asthma control and number of exacerbations. Demographics, current and past patient/family history, and clinical characteristics were collected. In addition, systems-wide omics layers, including epi(genomics), transcriptomics, microbiome, proteomics, and metabolomics were evaluated from multiple samples. In all, 145 children were included in this cohort, 91 with uncontrolled (median age = 12 years, 43% females) and 54 with controlled asthma (median age = 11.7 years, 37% females). The two groups did not show statistically significant differences in age, sex, and body mass index z-score distribution. Comprehensive information and diverse noninvasive biosampling procedures for various omics analyses will provide the opportunity to delineate underlying pathophysiological mechanisms of moderate-to-severe uncontrolled pediatric asthma. This eventually might reveal novel biomarkers, which could potentially be used for noninvasive personalized diagnostics and/or treatment.

Genetic effects of allergen-specific IgE levels on exhaled nitric oxide in schoolchildren with asthma: The STOPPA twin study

BACKGROUND

Exhaled nitric oxide and blood eosinophils are clinical asthma T-helper type 2 markers in use. Immunoglobulin E (IgE) is often involved in the inflammation associated with atopic asthma. The effect of both blood eosinophils and allergen-specific IgE on exhaled nitric oxide levels is not completely understood. Twin-design studies can improve understanding of the underlying contribution of genetically and/or environmentally driven inflammation markers in asthma. Our aim was to disentangle the covariance between asthma and exhaled nitric oxide into genetic and environmental contributions that can account for inflammation markers in a paediatric population.

METHODS

This population-based, cross-sectional twin study enrolled 612 monozygotic (MZ) and same-sex dizygotic (DZ) schoolchildren. Multivariate structural equation modelling was utilized to separate the covariance between asthma and exhaled nitric oxide into genetic and/or environmental effects, taking allergen-specific IgE level and blood eosinophil count into account while controlling for confounding factors.

RESULTS

The cross-twin/cross-trait correlations had a higher magnitude in the MZ twins than in the DZ twins, indicating that genes affect the association. The likelihood ratio test for model fitting resulted in the AE model (ie additive genetic effects, A, and non-shared environmental effects, E) as the most parsimonious. A majority, 73%, of the phenotypic correlation between asthma and exhaled nitric oxide, r = .19 (0.05-0.33), was attributable to genetic effects which mainly was due to the allergen-specific IgE level.

CONCLUSIONS

This study indicates that the association between asthma and exhaled nitric oxide in children is to a large extent explained by genetics via allergen-specific IgE level and not blood eosinophils. This might partly explain the clinical heterogeneity in this group. A next step could be to include allergen-specific IgE level in multivariate omic studies.

A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data

‘Asthma’ is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. Research to understand these phenotypes has previously been based on longitudinal wheeze patterns or hypothesis-driven observational criteria. The aim of this study was to use data-driven machine learning to identify asthma and wheeze phenotypes in children based on symptom and symptom history data, and, to further characterize these phenotypes. The study population included an asthma-rich population of twins in Sweden aged 9–15 years (n = 752). Latent class analysis using current and historical clinical symptom data generated asthma and wheeze phenotypes. Characterization was then performed with regression analyses using diagnostic data: lung function and immunological biomarkers, parent-reported medication use and risk-factors. The latent class analysis identified four asthma/wheeze phenotypes: early transient wheeze (15%); current wheeze/asthma (5%); mild asthma (9%), moderate asthma (10%) and a healthy phenotype (61%). All wheeze and asthma phenotypes were associated with reduced lung function and risk of hayfever compared to healthy. Children with mild and moderate asthma phenotypes were also more likely to have eczema, allergic sensitization and a family history of asthma. Furthermore, those with moderate asthma phenotype had a higher eosinophil concentration (β 0.21, 95%CI 0.12, 0.30) compared to healthy and used short-term relievers at a higher rate than children with mild asthma phenotype (RR 2.4, 95%CI 1.2–4.9). In conclusion, using a data driven approach we identified four wheeze/asthma phenotypes which were validated with further characterization as unique from one another and which can be adapted for use by the clinician or researcher.

The STOPPA Twin Study Explains the Exhaled Nitric Oxide and Asthma Link by Genetics and Sensitization

BACKGROUND

The link between asthma and exhaled nitric oxide (FENO) is not completely understood. The aim of this study was to estimate the association between FENO and asthma, taking genetics, sensitization, and inhaled corticosteroids (ICS) into account.

METHODS

A total of 681 twins (53% monozygotic [MZ] and 47% dizygotic [DZ]) from the population-based STOPPA study (mean age 12.6 years) were recruited and information on FENO (parts per billion), parental report of current asthma, sensitization to airborne allergens (Phadiatop; IgE ≥0.35 kUA/l), and ICS-treatment was collected. We estimated the association between FENO and asthma, sensitization, and ICS in all twins and within pairs (DZ and MZ) to address shared genetic and environmental factors. Linear regression of log-transformed FENO was used and results presented as exponentiated regression coefficients (exp[β]), with 95% confidence interval (CI).

RESULTS

We found an association between asthma and FENO in all twins, exp(β) 1.31 [1.11, 1.54]. In within-pairs analysis, the association was stronger within DZ pairs discordant for FENO, exp(β) 1.50 [1.19, 1.89], compared to MZ pairs, exp(β) 1.07 [0.84, 1.37], p = .049. There was no difference in FENO in non-sensitized children with asthma, compared to children with neither asthma nor sensitization, exp(β) 0.89 [0.77, 1.03]. However, increased FENO was associated with sensitization, exp(β) 1.48 [1.30, 1.69], and with sensitization together with asthma, exp(β) 1.98 [1.57, 2.51], in all twins and within DZ pairs discordant for FENO, but not in MZ pairs. The FENO asthma association remained in DZ pairs without regular ICS-treatment.

CONCLUSIONS

The association between FENO and asthma is explained by genetics and sensitization.

Associations Between Asthma and Sensitization to Pet or Pollen Allergens in Young Swedish Twins - The STOPPA Study

BACKGROUND

An association between childhood asthma and IgE sensitization has been established, but our understanding of the genetic and environmental contribution to it is incomplete. Our aim was to estimate the associations and dose-response relationship between asthma and sensitization to airborne allergens in Swedish 9- to 14-year-old twins. Additionally, we aimed to explore the importance of familial confounding from shared genes and environment using co-twin controls.

METHODS

In the STOPPA cohort, 752 same-sex twin children were screened with Phadiatop® (Thermo Fisher Scientific; Pharmacia, Uppsala, Sweden); if positive further analysis of IgE antibodies to airborne allergens of pets (cat, horse, dog), pollens (birch, timothy, mugwort), mites, and mold were performed. The associations between asthma and airborne allergens were assessed with generalized estimating equations. The co-twin control analysis was performed by conditional logistic regression.

RESULTS

Children with positive Phadiatop® had more than doubled odds of asthma (OR 2.53, 95% CI [1.74, 3.70]). Sensitization to pet allergens was associated with increased odds of asthma; for example, cat OR 4.15 (95% CI [2.67, 6.45]), with similar estimates for pollens; for example, birch OR 3.22 (95% CI [2.12, 4.91]). Associations persisted with sensitization as a categorical variable and for trend, indicating a dose-response relationship. Results remained in the co-twin analyses; for example, cat OR 4.75 (95% CI [1.62, 14.0]) and birch OR 5.00 (95% CI [1.45, 17.3]).

CONCLUSION

The association between childhood asthma and sensitization to airborne allergens remains in co-twin analyses, indicating they are not due to confounding from shared environmental or genetic factors.