A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development

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A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development
Title:
A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development
Journal Title:
Environmental Research
Keywords:
Publication Date:
19 February 2024
Citation:
Dong, Y., Lau, H. X., Suaini, N. H. A., Kee, M. Z. L., Ooi, D. S. Q., Shek, L. P., Lee, B. W., Godfrey, K. M., Tham, E. H., Ong, M. E. H., Liu, N., Wong, L., Tan, K. H., Chan, J. K. Y., Yap, F. K. P., Chong, Y. S., Eriksson, J. G., Feng, M., & Loo, E. X. L. (2024). A machine-learning exploration of the exposome from preconception in early childhood atopic eczema, rhinitis and wheeze development. Environmental Research, 250, 118523. https://doi.org/10.1016/j.envres.2024.118523
Abstract:
Background: Most previous research on the environmental epidemiology of childhood atopic eczema, rhinitis and wheeze is limited in the scope of risk factors studied. Our study adopted a machine learning approach to explore the role of the exposome starting already in the preconception phase. Methods: We performed a combined analysis of two multi-ethnic Asian birth cohorts, the Growing Up in Singapore Towards healthy Outcomes (GUSTO) and the Singapore PREconception Study of long Term maternal and child Outcomes (S-PRESTO) cohorts. Interviewer-administered questionnaires were used to collect information on demography, lifestyle and childhood atopic eczema, rhinitis and wheeze development. Data training was performed using XGBoost, genetic algorithm and logistic regression models, and the top variables with the highest importance were identified. Additive explanation values were identified and inputted into a final multiple logistic regression model. Generalised structural equation modelling with maternal and child blood micronutrients, metabolites and cytokines was performed to explain possible mechanisms. Results: The final study population included 1151 mother-child pairs. Our findings suggest that these childhood diseases are likely programmed in utero by the preconception and pregnancy exposomes through inflammatory pathways. We identified preconception alcohol consumption and maternal depressive symptoms during pregnancy as key modifiable maternal environmental exposures that increased eczema and rhinitis risk. Our mechanistic model suggested that higher maternal blood neopterin and child blood dimethylglycine protected against early childhood wheeze. After birth, early infection was a key driver of atopic eczema and rhinitis development. Conclusion: Preconception and antenatal exposomes can programme atopic eczema, rhinitis and wheeze development in utero. Reducing maternal alcohol consumption during preconception and supporting maternal mental health during pregnancy may prevent atopic eczema and rhinitis by promoting an optimal antenatal environment. Our findings suggest a need to include preconception environmental exposures in future research to counter the earliest precursors of disease development in children.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
This research / project is supported by the National Medical Research Council - Translational and Clinical Research (TCR) Flagship Program
Grant Reference no. : NMRC/TCR/004-NUS/2008

This research / project is supported by the National Medical Research Council - Translational and Clinical Research (TCR) Flagship Program
Grant Reference no. : NMRC/TCR/012-NUHS/2014

This research is supported by core funding from: Singapore Institute for Clinical Sciences
Grant Reference no. : NA

Supported by the UK Medical Research Council (MC_UU_12011/4), the National Institute for Health Research (NIHR Senior Investigator (NF–SI-0515-10042) and NIHR Southampton Biomedical Research Centre (NIHR203319)) and the European Union (Erasmus+ Programme ImpENSA 598488-EPP-1-2018-1-DE-EPPKA2-CBHE-JP).
Description:
ISSN:
0013-9351