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整个生命早期的社会经济地位预测疾病和衰老的基因表达特征。

Socioeconomic status across the early life course predicts gene expression signatures of disease and senescence.

机构信息

Erasmus School of Health Policy and Management, Erasmus Universiteit Rotterdam, Rotterdam, The Netherlands

Lausanne University Hospital, Lausanne, Switzerland.

出版信息

J Epidemiol Community Health. 2024 Nov 11;78(12):752-758. doi: 10.1136/jech-2023-221812.

Abstract

BACKGROUND

Socioeconomic status (SES) is associated with many chronic diseases, indicators of senescence and mortality. However, the changing salience of SES in the prediction of adult health is not well understood. Using mRNA-seq abundance data from wave V of the National Longitudinal Study of Adolescent to Adult Health (Add Health), we examine the extent to which SES across the early life course is related to gene expression-based signatures for chronic diseases, senescence and inflammation in the late 30s.

METHODS

We use Bayesian methods to identify the most likely model of life course epidemiology (critical, sensitive and accumulation models) that characterises the changing importance of parental SES and SES during young (ages 27-30) and mid-adulthood (ages 36-39) in the prediction of the signatures.

RESULTS

For most signatures, SES is an important predictor in all periods, although parental SES or SES during young adulthood are often the most predictive. For three signatures (components of diabetes, inflammation and ageing), critical period models involving the exclusive salience of SES in young adulthood (for diabetes) or parental SES (for inflammation and ageing) are most probable. The observed associations are likely mediated by body mass index.

CONCLUSION

Models of life course patterns of SES may inform efforts to identify age-specific mechanisms by which SES is associated with health at different points in life and they also suggest an enhanced approach to prediction models that recognise the changing salience of risk factors.

摘要

背景

社会经济地位(SES)与许多慢性疾病、衰老指标和死亡率有关。然而,SES 在预测成人健康方面的重要性变化尚不清楚。本研究使用青少年至成年健康纵向研究(Add Health)第五波的 mRNA-seq 丰度数据,研究了整个生命历程中的 SES 与 30 多岁时慢性疾病、衰老和炎症的基于基因表达的特征之间的关系。

方法

我们使用贝叶斯方法来确定最有可能的生命历程流行病学模型(关键、敏感和积累模型),以描述在预测特征时,父母 SES 和青年期(27-30 岁)和中年期(36-39 岁) SES 的重要性变化。

结果

对于大多数特征,SES 在所有时期都是一个重要的预测因素,尽管父母 SES 或青年期 SES 通常是最具预测性的。对于三个特征(糖尿病、炎症和衰老的组成部分),涉及青年期 SES (糖尿病)或父母 SES (炎症和衰老)的唯一重要性的关键期模型是最有可能的。观察到的关联可能是通过体重指数介导的。

结论

SES 的生命历程模式模型可以为识别 SES 与不同生命阶段健康相关的特定年龄机制的努力提供信息,并且还表明了一种增强的预测模型方法,该方法认识到风险因素的重要性变化。

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