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

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.

• Böck, A.
• Urner, K.
• Eckert, J. K.
• Salvermoser, M.
• Laubhahn, K.
• Kunze, S.
• Kumbrink, J.
• Hoeppner, M. P.
• Kalkbrenner, K.
• Kreimeier, S.
• Beyer, K.
• Hamelmann, E.
• Kabesch, M.
• Depner, M.
• Hansen, G.
• Riedler, J.
• Roponen, M.
• Schmausser-Hechfellner, E.
• Barnig, C.
• Divaret-Chauveau, A.
• Karvonen, A. M.
• Pekkanen, J.
• Frei, R.
• Roduit, C.
• Lauener, R.
• Schaub, B.