Evolution of Eczema, Wheeze, and Rhinitis from Infancy to Early Adulthood Four Birth Cohort Studies

Funding Information: Supported by the UK Medical Research Council (MRC) Programme grant MR/S025340/1 (UNICORN consortium); MRC grants G0601361 and MR/ K002449/1 (STELAR consortium); Wellcome Trust Strategic Award 108818/15/Z (R.G.); Asthma UK grants no. 301 (1995–1998), 362 (1998–2001), 01/012 (2001–2004), and 04/014 (2004–2007) (MAAS); BMA James Trust (2005), the JP Moulton Charitable Foundation (2004–2016), The North West Lung Centre Charity (1997–current), and MRC grant MR/L012693/1 (2014–2018) (MAAS); and the Isle of Wight Health Authority, the National Asthma Campaign, UK grant no. 364, and NIH grants R01 HL082925-01, R01 AI091905, and R01 AI121226 (IOW). Funding Information: Author Contributions: A.C., A.S., S.H., and S.F. conceived and planned the study and wrote the manuscript. S.H., S.F., and G.H. analyzed the data. All authors contributed to the interpretation of the results. All authors provided critical feedback and helped shape the research, analysis, and manuscript. A.S. and C.S.M. are supported by the National Institute for Health Research Manchester Biomedical Research Centre. Publisher Copyright: Copyright © 2022 by the American Thoracic Society.Peer reviewedPublisher PD

Development of childhood asthma prediction models using machine learning approaches

Background: Respiratory symptoms are common in early life and often transient. It is difficult to identify in which children these will persist and result in asthma. Machine learning (ML) approaches have the potential for better predictive performance and generalisability over existing childhood asthma prediction models. This study applied ML approaches to predict school-age asthma (age 10) in early life (Childhood Asthma Prediction in Early life, CAPE model) and at preschool age (Childhood Asthma Prediction at Preschool age, CAPP model). Methods: Clinical and environmental exposure data was collected from children enrolled in the Isle of Wight Birth Cohort (N = 1368, ∼15% asthma prevalence). Recursive Feature Elimination (RFE) identified an optimal subset of features predictive of school-age asthma for each model. Seven state-of-the-art ML classification algorithms were used to develop prognostic models. Training was performed by applying fivefold cross-validation, imputation, and resampling. Predictive performance was evaluated on the test set. Models were further externally validated in the Manchester Asthma and Allergy Study (MAAS) cohort. Results: RFE identified eight and twelve predictors for the CAPE and CAPP models, respectively. Support Vector Machine (SVM) algorithms provided the best performance for both the CAPE (area under the receiver operating characteristic curve, AUC = 0.71) and CAPP (AUC = 0.82) models. Both models demonstrated good generalisability in MAAS (CAPE 8-year = 0.71, 11-year = 0.71, CAPP 8-year = 0.83, 11-year = 0.79) and excellent sensitivity to predict a subgroup of persistent wheezers. Conclusion: Using ML approaches improved upon the predictive performance of existing regression-based models, with good generalisability and ability to rule in asthma and predict persistent wheeze.</p

Obstructive and restrictive spirometry from school age to adulthood: three birth cohort studies

Background: Spirometric obstruction and restriction are two patterns of impaired lung function which are predictive of poor health. We investigated the development of these phenotypes and their transitions through childhood to early adulthood. Methods: In this study, we analysed pooled data from three UK population−based birth cohorts established between 1989 and 1995. We applied descriptive statistics, regression modelling and data-driven modelling to data from three population−based birth cohorts with at least three spirometry measures from childhood to adulthood (mid-school: 8–10 years, n = 8404; adolescence: 15–18, n = 5764; and early adulthood: 20–26, n = 4680). Participants were assigned to normal, restrictive, and obstructive spirometry based on adjusted regression residuals. We considered two transitions: from 8–10 to 15–18 and from 15–18 to 20–26 years. Findings: Obstructive phenotype was observed in ∼10%, and restrictive in ∼9%. A substantial proportion of children with impaired lung function in school age (between one third in obstructive and a half in restricted phenotype) improved and achieved normal and stable lung function to early adulthood. Of those with normal lung function in school-age, <5% declined to adulthood. Underweight restrictive and obese obstructive participants were less likely to transit to normal. Maternal smoking during pregnancy and current asthma diagnosis increased the risk of persistent obstruction and worsening. Significant associate of worsening in restrictive phenotypes was lower BMI at the first lung function assessment. Data-driven methodologies identified similar risk factors for obstructive and restrictive clusters. Interpretation: The worsening and improvement in obstructive and restrictive spirometry were observed at all ages. Maintaining optimal weight during childhood and reducing maternal smoking during pregnancy may reduce spirometry obstruction and restriction and improve lung function. Funding: MRC Grant MR/S025340/1

Integration of genomic risk scores to improve the prediction of childhood asthma diagnosis

Genome-wide and epigenome-wide association studies have identified genetic variants and differentially methylated nucleotides associated with childhood asthma. Incorporation of such genomic data may improve performance of childhood asthma prediction models which use phenotypic and environmental data. Using genome-wide genotype and methylation data at birth from the Isle of Wight Birth Cohort (n = 1456), a polygenic risk score (PRS), and newborn (nMRS) and childhood (cMRS) methylation risk scores, were developed to predict childhood asthma diagnosis. Each risk score was integrated with two previously published childhood asthma prediction models (CAPE and CAPP) and were validated in the Manchester Asthma and Allergy Study. Individually, the genomic risk scores demonstrated modest-to-moderate discriminative performance (area under the receiver operating characteristic curve, AUC: PRS = 0.64, nMRS = 0.55, cMRS = 0.54), and their integration only marginally improved the performance of the CAPE (AUC: 0.75 vs. 0.71) and CAPP models (AUC: 0.84 vs. 0.82). The limited predictive performance of each genomic risk score individually and their inability to substantially improve upon the performance of the CAPE and CAPP models suggests that genetic and epigenetic predictors of the broad phenotype of asthma are unlikely to have clinical utility. Hence, further studies predicting specific asthma endotypes are warranted.</p

Dog ownership in infancy is protective for persistent wheeze in 17q21 asthma-risk carriers

Background: asthma-associated SNPs from large GWAS studies only explain a fraction of genetic heritability. Likely causes of the missing heritability include broad phenotype definitions and gene-environment interactions (GxE). The mechanisms underlying GxE in asthma are poorly understood. Previous GxE studies on pet ownership showed discordant results.Objectives: to study the GxE between the 17q12-21 locus and pet ownership in infancy in relation to wheeze.Methods: wheezing classes derived from five UK-based birth cohorts (latent class analysis) were used to study GxE between the 17q12-21 asthma-risk variant rs2305480 and dog and cat ownership in infancy, using multinomial logistic regression. 9149 children had both pet ownership and genotype data available. Summary statistics from individual analyses were meta-analysed.Results: rs2305480 G allele was associated with increased risk of Persistent Wheeze (additive model OR=1.37; CI=1.25-1.51). There was no evidence of an association between dog or cat ownership and wheeze. We found significant evidence of a GxE interaction between rs2305480 and dog ownership (P=8.3e-4) on Persistent Wheeze; amongst dog owners the G allele was no longer associated with an increased risk of Persistent Wheeze (additive model OR=0.95; CI=0.73-1.24). For those without pets, G allele was associated with increased risk of Persistent Wheeze (OR=1.61; CI=1.40-1.86). Amongst cat owners no such dampening of the genetic effect was observed.Conclusions: amongst dog owners, rs2305480 G was no longer associated with an increased risk of Persistent Wheeze (or asthma). Early life environmental exposures may therefore attenuate likelihood of asthma in those carrying 17q12-21 risk alleles.</p

Lung function trajectories from school age to adulthood and their relationship with markers of cardiovascular disease risk

Rationale: Lung function in early adulthood is associated with subsequent adverse health outcomes. Objectives: To ascertain whether stable and reproducible lung function trajectories can be derived in different populations and investigate their association with objective measures of cardiovascular structure and function. Methods: Using latent profile modelling, we studied three population-based birth cohorts with repeat spirometry data from childhood into early adulthood to identify trajectories of forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC). We used multinomial logistic regression models to investigate early-life predictors of the derived trajectories. We then ascertained the extent of the association between the derived FEV1/FVC trajectories and blood pressure and echocardiographic markers of increased cardiovascular risk and stroke in ∼3200 participants at age 24 years in one of our cohorts. Results: We identified four FEV1/FVC trajectories with strikingly similar latent profiles across cohorts (pooled N=6377): above average (49.5%); average (38.3%); below average (10.6%); and persistently low (1.7%). Male sex, wheeze, asthma diagnosis/medication and allergic sensitisation were associated with trajectories with diminished lung function in all cohorts. We found evidence of an increase in cardiovascular risk markers ascertained by echocardiography (including left ventricular mass indexed to height and carotid intima-media thickness) with decreasing FEV1/FVC (with p values for the mean crude effects per-trajectory ranging from 0.10 to p&lt;0.001). In this analysis, we considered trajectories as a pseudo-continuous variable; we confirmed the assumption of linearity in all the regression models. Conclusions: Childhood lung function trajectories may serve as predictors in the development of not only future lung disease, but also the cardiovascular disease and multimorbidity in adulthood.</p