Obesity Risk in Young Adults from the Jerusalem Perinatal Study (JPS): the Contribution of Polygenic Risk and Early Life Exposure

Overview

Journal Int J Obes (Lond)

Specialty Endocrinology

Date 2024 Mar 13

PMID 38472354

Authors

Hagit Hochner

Rachely Butterman

Ido Margaliot

Yechiel Friedlander

Michal Linial

Affiliations

Soon will be listed here.

Abstract

Background/objectives: The effects of early life exposures on offspring life-course health are well established. This study assessed whether adding early socio-demographic and perinatal variables to a model based on polygenic risk score (PRS) improves prediction of obesity risk.

Methods: We used the Jerusalem Perinatal study (JPS) with data at birth and body mass index (BMI) and waist circumference (WC) measured at age 32. The PRS was constructed using over 2.1M common SNPs identified in genome-wide association study (GWAS) for BMI. Linear and logistic models were applied in a stepwise approach. We first examined the associations between genetic variables and obesity-related phenotypes (e.g., BMI and WC). Secondly, socio-demographic variables were added and finally perinatal exposures, such as maternal pre-pregnancy BMI (mppBMI) and gestational weight gain (GWG) were added to the model. Improvement in prediction of each step was assessed using measures of model discrimination (area under the curve, AUC), net reclassification improvement (NRI) and integrated discrimination improvement (IDI).

Results: One standard deviation (SD) change in PRS was associated with a significant increase in BMI (β = 1.40) and WC (β = 2.45). These associations were slightly attenuated (13.7-14.2%) with the addition of early life exposures to the model. Also, higher mppBMI was associated with increased offspring BMI (β = 0.39) and WC (β = 0.79) (p < 0.001). For obesity (BMI ≥ 30) prediction, the addition of early socio-demographic and perinatal exposures to the PRS model significantly increased AUC from 0.69 to 0.73. At an obesity risk threshold of 15%, the addition of early socio-demographic and perinatal exposures to the PRS model provided a significant improvement in reclassification of obesity (NRI, 0.147; 95% CI 0.068-0.225).

Conclusions: Inclusion of early life exposures, such as mppBMI and maternal smoking, to a model based on PRS improves obesity risk prediction in an Israeli population-sample.

Citing Articles

Genetic contributions to body mass index over adolescence and its associations with adult weight gain: a 25-year follow-up study of Finnish twins.

Obeso A, Drouard G, Jelenkovic A, Aaltonen S, Palviainen T, Salvatore J Int J Obes (Lond). 2024; 49(2):357-363.

PMID: 39567637 PMC: 11805703. DOI: 10.1038/s41366-024-01684-3.

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