An integrated molecular risk score early in life for subsequent childhood asthma risk

Andreas Böck; Kathrin Urner; Jana Kristin Eckert; Michael Salvermoser; Kristina Laubhahn; Sonja Kunze; Jörg Kumbrink; Marc P Hoeppner; Kathrin Kalkbrenner; Simone Kreimeier; Kirsten Beyer; Eckard Hamelmann; Michael Kabesch; Martin Depner; Gesine Hansen; Josef Riedler; Marjut Roponen; Elisabeth Schmausser-Hechfellner; Cindy Barnig; Amandine Divaret-Chauveau; Anne M Karvonen; Juha Pekkanen; Remo Frei; Caroline Roduit; Roger Lauener; Bianca Schaub; CHAMP study group; PASTURE study group

doi:10.1111/cea.14475

An integrated molecular risk score early in life for subsequent childhood asthma risk

Clin Exp Allergy. 2024 May;54(5):314-328. doi: 10.1111/cea.14475. Epub 2024 Mar 31.

Authors

Andreas Böck^{1

2}, Kathrin Urner^{1

2}, Jana Kristin Eckert^{1

2}, Michael Salvermoser^{1

2}, Kristina Laubhahn^{1

3}, Sonja Kunze^{4

5}, Jörg Kumbrink⁶, Marc P Hoeppner⁷, Kathrin Kalkbrenner^{1

2}, Simone Kreimeier^{2

8}, Kirsten Beyer^{2

9}, Eckard Hamelmann^{2

10}, Michael Kabesch^{2

11}, Martin Depner^{2

12}, Gesine Hansen^{2

13

14

15}, Josef Riedler¹⁶, Marjut Roponen¹⁷, Elisabeth Schmausser-Hechfellner¹², Cindy Barnig^{18

19}, Amandine Divaret-Chauveau^{20

21

22}, Anne M Karvonen²³, Juha Pekkanen^{23

24}, Remo Frei^{25

26}, Caroline Roduit^{25

26

27

28}, Roger Lauener^{25

27}, Bianca Schaub^{1

2

3}; CHAMP study group; PASTURE study group

Collaborators

Affiliations

¹ Pediatric Allergology, Department of Pediatrics, Dr. von Hauner Children's Hospital, University Hospital, LMU Munich, Munich, Germany.
² Member of the CHildhood Allergy and Tolerance Consortium (CHAMP), LMU Munich, Munich, Germany.
³ Comprehensive Pneumology Center - Munich (CPC-M), German Center for Lung Research (DZL), Munich, Germany.
⁴ Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
⁵ Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
⁶ Institute of Pathology, Medical Faculty, LMU Munich, Munich, Germany.
⁷ Institute of Clinical Molecular Biology, Christian-Albrechts-Universität zu Kiel, Kiel, Germany.
⁸ Department of Health Economics and Health Care Management, School of Public Health, Bielefeld University, Bielefeld, Germany.
⁹ Department of Pediatric Respiratory Medicine, Immunology and Critical Care Medicine, Charité Universitätsmedizin Berlin, Berlin, Germany.
¹⁰ Department for Pediatrics, Children's Center Bethel, University Hospital OWL, Bielefeld University, Bielefeld, Germany.
¹¹ University Children's Hospital Regensburg (KUNO), St. Hedwig's Hospital of the Order of St. John and the University of Regensburg, Regensburg, Germany.
¹² Institute of Asthma and Allergy Prevention, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.
¹³ Department of Pediatric Pneumology, Allergology and Neonatology, Hannover Medical School, Hannover, Germany.
¹⁴ Biomedical Research in Endstage and Obstructive Lung Disease Biomedical Research in Endstage and Obstructive Lung Disease (BREATH), Member of the German Center for Lung Research (DZL), Hannover, Germany.
¹⁵ Excellence Cluster Resolving Infection Susceptibility RESIST (EXC 2155), Deutsche Forschungsgemeinschaft, Hannover Medical School, Hannover, Germany.
¹⁶ Children's Hospital Schwarzach, Schwarzach, Austria.
¹⁷ Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, Finland.
¹⁸ Department of Respiratory Disease, University Hospital, Besanҫon, France.
¹⁹ INSERM, EFS BFC, LabEx LipSTIC, UMR1098, Interactions Hôte-Greffon-Tumeur/Ingénierie Cellulaire et Génique, Univ. Bourgogne Franche-Comté, Besançon, France.
²⁰ Pediatric Allergy Department, Children's Hospital, University Hospital of Nancy, Vandoeuvre les Nancy, France.
²¹ EA3450 Development, Adaptation and Handicap (devah), Pediatric Allergy Department, University of Lorraine, Nancy, France.
²² UMR/CNRS 6249 Chrono-environment, University of Franche Comté, Besançon, France.
²³ Department of Health Security, Finnish Institute for Health and Welfare, Kuopio, Finland.
²⁴ Department of Public Health, University of Helsinki, Helsinki, Finland.
²⁵ Christine Kühne Center for Allergy Research and Education (CK-CARE), Davos, Switzerland.
²⁶ Division of Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, University of Bern, Bern, Switzerland.
²⁷ Children's Hospital of Eastern Switzerland, St. Gallen, Switzerland.
²⁸ Children's Hospital, University of Zürich, Zürich, Switzerland.

PMID: 38556721
DOI: 10.1111/cea.14475

Abstract

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.

Keywords: asthma; epidemiology; genetics; paediatrics; prevention.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Asthma* / diagnosis
Asthma* / epidemiology
Asthma* / genetics
Biomarkers
Birth Cohort
Child
Child, Preschool
DNA Methylation
Female
Humans
Longitudinal Studies
Male
Risk Factors

Substances

Biomarkers

Abstract

Publication types

MeSH terms

Substances

Grants and funding