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Published on: August 7, 2017
An integrated molecular risk score early in life for subsequent childhood asthma risk
Andreas Böck1,2, Kathrin Urner1,2, Jana Kristin Eckert1,2
1Pediatric Allergology, Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, LMU Munich, Munich, Germany.
Insights
Predicting childhood asthma is crucial for early intervention. While molecular markers offer modest improvements, combining birth risk factors with later allergic symptoms significantly enhances prediction accuracy.
Area of Science:
- Pediatric Allergy and Immunology
- Genetics and Genomics
- Epidemiology
Background:
- Childhood asthma affects a significant subgroup of children with early wheeze.
- Early identification of at-risk children is vital for timely management and preventing severe outcomes.
- Integrating genetic and clinical data aids in predicting childhood asthma development.
Purpose of the Study:
- To develop an integrated risk score for predicting childhood asthma.
- To combine established risk factors, genome-wide molecular markers at birth, and subsequent clinical symptoms for improved prediction.
Main Methods:
- Utilized three longitudinal birth cohorts (PAULINA/PAULCHEN, PASTURE) with epidemiological and molecular data (genotype, DNA methylation, mRNA expression).
- Employed Naïve-Bayes and LASSO regression models for apparent and optimism-corrected performance assessment (AUC/R2).
- Analyzed longitudinal mRNA expression changes from cord blood to age six in the PASTURE cohort.
Main Results:
- Epidemiological factors at birth predicted asthma with an optimism-corrected AUC (ocAUC) of 0.65.
- Molecular markers modestly improved prediction (ocAUC up to 0.68).
- Inclusion of early allergic symptoms/diagnoses significantly enhanced prediction power (ocAUC up to 0.76).
- Longitudinal mRNA expression at age six showed the strongest association with asthma, with increasing gene correlations over time.
Conclusions:
- Epidemiological predictors alone offer moderate asthma prediction.
- Molecular markers at birth provide a modest enhancement to prediction models.
- Allergic symptoms/diagnoses are key predictors, improving model performance significantly for clinical application and future research.
Background:
Numerous children present with early wheeze symptoms, yet solely a subgroup develops childhood asthma. Early identification of children at risk is key for clinical monitoring, timely patient-tailored treatment, and preventing chronic, severe sequelae. For early prediction of childhood asthma, we aimed to define an integrated risk score combining established risk factors with genome-wide molecular markers at birth, complemented by subsequent clinical symptoms/diagnoses (wheezing, atopic dermatitis, food allergy).
Methods:
Three longitudinal birth cohorts (PAULINA/PAULCHEN, n = 190 + 93 = 283, PASTURE, n = 1133) were used to predict childhood asthma (age 5-11) including epidemiological characteristics and molecular markers: genotype, DNA methylation and mRNA expression (RNASeq/NanoString). Apparent (ap) and optimism-corrected (oc) performance (AUC/R2) was assessed leveraging evidence from independent studies (Naïve-Bayes approach) combined with high-dimensional logistic regression models (LASSO).
Results:
Asthma prediction with epidemiological characteristics at birth (maternal asthma, sex, farm environment) yielded an ocAUC = 0.65. Inclusion of molecular markers as predictors resulted in an improvement in apparent prediction performance, however, for optimism-corrected performance only a moderate increase was observed (upto ocAUC = 0.68). The greatest discriminate power was reached by adding the first symptoms/diagnosis (up to ocAUC = 0.76; increase of 0.08, p = .002). Longitudinal analysis of selected mRNA expression in PASTURE (cord blood, 1, 4.5, 6 years) showed that expression at age six had the strongest association with asthma and correlation of genes getting larger over time (r = .59, p < .001, 4.5-6 years).
Conclusion:
Applying epidemiological predictors alone showed moderate predictive abilities. Molecular markers from birth modestly improved prediction. Allergic symptoms/diagnoses enhanced the power of prediction, which is important for clinical practice and for the design of future studies with molecular markers.
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