Toward a more holistic approach to the study of exposures and child outcomes

Abstract

Aim: The current work was designed to demonstrate the application of the exposome framework in examining associations between exposures and children's long-term neurodevelopmental and behavioral outcomes. Methods: Longitudinal data were collected from birth through age 6 from 402 preterm infants. Three statistical methods were utilized to demonstrate the exposome framework: exposome-wide association study, cumulative exposure and machine learning models, with and without epigenetic data. Results: Each statistical approach answered a distinct research question regarding the impact of exposures on longitudinal child outcomes. Findings highlight associations between exposures, epigenetics and executive function. Conclusion: Findings demonstrate how an exposome-based approach can be utilized to understand relationships between internal (e.g., DNA methylation) and external (e.g., prenatal risk) exposures and long-term developmental outcomes in preterm children.

Summary points

• Environmental and psychosocial exposures have been recognized as important predictors of chronic disease risk and neurodevelopmental outcomes.

• The exposome is an established conceptual model that systematically examines the combined effects of biological, psychological, environmental and social exposures on health, well-being and development.

• This work was designed to apply the exposome framework to children's behavioral and neurodevelopmental outcomes and provide a roadmap for statistical approaches to assessing exposure-outcome relationships.

• Data was collected from a cohort of very preterm infants and included pre- and peri-natal exposure variables and behavioral and neurodevelopmental outcomes. Genomic DNA was collected from neonates for genome-wide DNA methylation analysis.

• Application of the exposome framework was demonstrated via three statistical approaches: exposome-wide association study, cumulative exposure models and random forest machine learning models. These techniques were then expanded to consider the joint role of exposures and epigenetics as predictors of child neurobehavioral outcomes.

• The results demonstrated the ability of an exposome-wide association study model to identify a cluster of exposure variables associated with child executive function. These findings were corroborated by findings from the cumulative exposure and machine learning models, suggesting that perinatal exposures predicted child executive function.

• Joint models showed independent and, potentially, interactive effects of exposures and epigenetic patterns on outcomes.

• These findings demonstrate the utility of the exposome framework for more holistically studying associations between exposures and child health and neurobehavioral outcomes.

Keywords: :

• epigenetics
• exposome
• machine learning
• neurodevelopment
• prematurity

Author contributions

All authors initiated and designed this investigation, contributed to interpretation of the results, revisions to the manuscript and approval of the final version. BM Lester, CJ Marsit, TM Everson and M Camerota acquired funding for this study and M Camerota, TM Everson and CL Shuster conducted the statistical analysis.

Financial disclosure

This work was funded by the National Institutes of Health/Eunice Kennedy Shriver National Institute of Child Health and Human Development grant R01HD072267 (BM Lester and O'Shea ), UH3OD023347 (BM Lester and CJ Marsit) and R01HD084515 (BM Lester and TM Everson) and National Institute of Mental Health grant K01MH129510 (M Camerota). The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Competing interests disclosure

The authors have no competing interests or relevant affiliations with any organization or entity with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Writing disclosure

No writing assistance was utilized in the production of this manuscript.

Ethical conduct of research

The authors state that institutional review board approval was received from Children's Mercy Hospital, Los Angeles Biomedical Research Institute, Memorial Care Health System, Western Institutional Review Board, Spectrum Health, University of North Carolina–Chapel Hill, Wake Forest University Health Services and Women and Infants Hospital of Rhode Island for the research described. In addition, verbal and written informed consent was obtained from all participants for the inclusion of their data within this work.

Data sharing statement

The microarray data generated and/or analyzed in the current study are available in the National Center for Biotechnology Information Gene Expression Omnibus (accession series GSE128821). R codes used for the analyses presented in this paper are available upon request from the corresponding author.

Additional information

Funding

his work was funded by the National Institutes of Health/Eunice Kennedy Shriver National Institute of Child Health and Human Development grant R01HD072267 (BM Lester and O'Shea ), UH3OD023347 (BM Lester and CJ Marsit) and R01HD084515 (BM Lester and TM Everson) and National Institute of Mental Health grant K01MH129510 (M Camerota).