青年期肥胖风险的研究：耶路撒冷围产研究（JPS）的多基因风险和生命早期暴露的作用。

Obesity risk in young adults from the Jerusalem Perinatal Study (JPS): the contribution of polygenic risk and early life exposure.

机构信息

Braun School of Public Health, Hebrew University of Jerusalem, Jerusalem, Israel.

Department of Biological Chemistry, Institute of Life Sciences, The Hebrew University of Jerusalem, 91904, Jerusalem, Israel.

出版信息

Int J Obes (Lond). 2024 Jul;48(7):954-963. doi: 10.1038/s41366-024-01505-7. Epub 2024 Mar 12.

DOI:10.1038/s41366-024-01505-7

PMID:38472354

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11216986/

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.

摘要

背景/目的：早期生活经历对后代生命过程健康的影响已得到充分证实。本研究评估了在基于多基因风险评分（PRS）的模型中添加早期社会人口学和围产期变量是否可以提高肥胖风险预测的准确性。

方法

我们使用耶路撒冷围产期研究（JPS）的数据，这些数据包括出生时以及 32 岁时的体重指数（BMI）和腰围（WC）。PRS 是使用全基因组关联研究（GWAS）中超过 210 万个常见 SNP 构建的，这些 SNP 与 BMI 相关。线性和逻辑模型采用逐步方法进行应用。我们首先检查了遗传变量与肥胖相关表型（如 BMI 和 WC）之间的关联。其次，添加了社会人口统计学变量，最后将围产期暴露（如母亲孕前 BMI（mppBMI）和妊娠体重增加（GWG））添加到模型中。通过评估模型区分度（曲线下面积，AUC）、净重新分类改善（NRI）和综合判别改善（IDI）来评估每个步骤的预测改善情况。

结果

PRS 每增加一个标准差（SD），BMI（β=1.40）和 WC（β=2.45）就会显著增加。将早期生活暴露因素添加到模型中后，这些关联略有减弱（13.7-14.2%）。此外，较高的 mppBMI 与后代 BMI（β=0.39）和 WC（β=0.79）的增加有关（p<0.001）。对于肥胖（BMI≥30）预测，将早期社会人口学和围产期暴露因素添加到 PRS 模型中，AUC 从 0.69 增加到 0.73。在肥胖风险阈值为 15%时，将早期社会人口学和围产期暴露因素添加到 PRS 模型中，可以显著改善肥胖的重新分类（NRI，0.147；95%CI 0.068-0.225）。