Logo image
The predictive utility of the in utero exposome for childhood adiposity in independent and integrated frameworks
Journal article   Peer reviewed

The predictive utility of the in utero exposome for childhood adiposity in independent and integrated frameworks

Jonathan VanHawkins, Ryan Peterson, Kylie Harrall, Brandy Moon, Dana Dabelea, Katerina Kechris and Wei Perng
Pediatric obesity, Vol.19(12), pp.e13172-n/a
12/01/2024
DOI: 10.1111/ijpo.13172
PMCID: PMC11560695
PMID: 39327854
url
https://pmc.ncbi.nlm.nih.gov/articles/PMC11560695/pdf/nihms-2021322.pdfView
Open Access

Abstract

ObjectivesTo assess the predictive potential of the in utero exposome in relation to childhood adiposity as indicated by body mass index z-scores (BMIz) and the fourth versus first quartile of % fat mass (FM) at median age of 4.6 years.MethodsWe leveraged data on clinical risk factors for childhood obesity during the perinatal period, along with cord blood per/polyfluoroalkyl substances (PFAS) and cord blood DNA methylation, in 268 mother-offspring pairs. We used the sparsity ranked LASSO penalized regression framework for each outcome and assessed model performance based on % variability explained for BMIz and area under the receiver operating characteristic curve (AUC) for the fourth versus first quartile of %FM. We employed cross-validation for model tuning and split-sample validation for model evaluation.ResultsMean +/- SD BMIz was 0.01 +/- 1.1, %FM was 19.8 +/- 6.34%. The optimal model for predicting BMIz explained 19.1% of the variability in the validation set and included only clinical characteristics: maternal pre-pregnancy BMI, paternal BMI, gestational weight gain, physical activity during pregnancy and child race/ethnicity. The optimal model for fourth versus first quartiles of %FM achieved an AUC of 0.82 +/- 0.01 in the validation set, with the clinical features again emerging as the strongest predictors.ConclusionIn this study sample, perinatal chemical exposures and the epigenome have low utility in predicting childhood adiposity, beyond known clinical risk factors.
Life Sciences & Biomedicine Pediatrics Science & Technology

Details

Metrics

2 Record Views
4 readers on Mendeley
Logo image