社会与工程心理学研究室知识库

抑郁和焦虑对个体与社会造成了沉重的负担，并且存在高共病性。抑郁和焦虑在很大程度上受到遗传因素的影响，可以通过多基因风险评分(polygenic risk score, PRS)来量化个体的遗传风险。同时，个体的社会经济地位(socio-economic status, SES)（个体 SES）与个体当前生活区域的社会经济发展程度（区域 SES） 这两类环境因素也会对抑郁和焦虑产生广泛而深远的影响。但是，目前关于 PRS、 个体 SES 或区域 SES 对抑郁和焦虑影响的研究存在许多不一致的结果，且大部 分研究往往只聚焦于遗传、个体 SES 和区域 SES 中的一个或两个层面。因此，本研究旨在综合这三个层面，在中国成年人群体中，较为全面地考察全基因组遗 传风险、多项个体 SES 指标和多项区域 SES 指标对抑郁和焦虑情绪的影响以及其中的交互作用。

研究一旨在从遗传角度探究抑郁、焦虑和神经质的 PRS 能否有效预测个体 的抑郁和焦虑症状。为此，我们从基因检测公司的客户群中招募了 2134 名被试，对他们近期的抑郁和焦虑症状进行了问卷调查，并获取了他们的全基因组检测结果。然后，基于抑郁、焦虑和神经质的全基因组关联研究(genome-wide association study, GWAS)元分析结果，我们计算了每名被试的相应表型PRS。分析结果表明， 神经质 PRS 能显著正向预测中国个体的抑郁和焦虑情绪，抑郁症状 PRS 能显著 正向预测中国个体的焦虑情绪，其中神经质 PRS 表现出最强的预测能力。

研究二主要考察个体 SES、区域 SES、以及两者的交互作用如何预测抑郁和焦虑情绪。研究二与研究一采用了相同的样本，共有 2090 名被试符合纳入标准。采用多元线性回归模型进行数据分析。结果发现，在各项个体 SES 指标中，对原 生家庭的主观社会地位(subjective social status, SSS)显著负向预测个体当前的抑 郁和焦虑症状，母亲受教育水平显著正向预测个体的抑郁和焦虑症状，父亲受教 育水平显著正向预测个体的焦虑症状，个体当前收入显著负向预测个体的抑郁症状，个体受教育水平则可以显著负向预测个体的抑郁和焦虑症状。区域 SES 中，个体当前长期生活省份的人均国内生产总值(gross domestic product, GDP)、平均 受教育年限和汤森剥夺指数均不能显著预测抑郁或焦虑。但是，个体 SES 与区 域 SES 存在显著的交互作用。具体表现为，高区域经济水平对抑郁症状有保护 作用，但这种关联仅存在于低受教育水平人群中；此外，对于原生家庭 SSS 较高的个体而言，当他们生活在教育水平较低的区域内时，其抑郁症状显著更少，与 “宁做鸡头，不做凤尾”的成语恰恰相符。 研究三拟探讨基因与环境如何共同作用于抑郁和焦虑，重点分析 PRS与个体 SES、区域 SES 之间是否存在交互作用。

研究三采用了研究二中的 2090 名被试，并基于研究一和研究二的结果选择 PRS 变量和 SES 变量，运用多元线性回归模型进行分析。研究结果表明，基因与环境之间存在显著的交互作用：高原生 家庭 SSS 可以预测低焦虑症状，但这种关联仅存在于遗传风险中等或较高的人群中；同时，高个体受教育水平也可以预测低焦虑症状，但这一关联仅在遗传风 险中等的人群中发现。

总体而言，本研究结果表明，抑郁症状 PRS 和神经质 PRS 能有效预测中国人的抑郁或焦虑症状；不同 SES 变量对抑郁和焦虑症状的影响存在差异；个体 SES 和区域 SES 之间存在交互作用；PRS 与原生家庭 SES、个体当前 SES 之 也存在基因-环境交互作用。本研究的主要创新点在于，应用了前沿的 PRS 分方法，结合个体与区域两个水平的 SES，从微观的遗传分子到宏观的区域 SES 个层次探讨了遗传与环境对抑郁、焦虑的影响，并揭示了基因-环境交互作用及环境-环境交互作用。通过加深对抑郁、焦虑发生机制的认识，本研究为制定心理健康的预防、干预措施与公共卫生政策提供了理论指导，也对当前国民广泛关注的议题，如原生家庭如何影响个体的心理健康、大学生毕业后是否留在大城市等，提供了有力的科学参考。

Depression and anxiety impose a heavy burden on both individuals and society, and are highly comorbid. They are largely influenced by genetic factors. An individual's genetic predisposition to depression and anxiety can be quantified by polygenic risk score (PRS). Additionally, environmental factors, including individual-level socioeconomic status (individual SES) and the socio-economic development level of one's current living area (area SES), also have a broad and far-reaching impact on depression and anxiety. However, existing researches on the effects of PRS, individual SES, and area SES on depression and anxiety yield inconsistent results. And most studies focus on only one or two levels of gene, individual SES, and area SES. Therefore, this study aims to integrate these three levels to thoroughly investigate the effects and interactions of genome-wide genetic risk, individual SES variables and area SES variables on depression and anxiety in Chinese adults.

Study 1 aims to explore whether PRS of depression, anxiety, and neuroticism can effectively predict individual depressive and anxiety symptoms from the genetic aspect. Employing a sample of 2,134 subjects from a genetics company's clientele, we conducted questionnaire surveys to evaluate their recent depressive and anxiety symptoms, and obtained their genome-wide test results. Then, based on the results of meta-analyses of genome-wide association studies (GWAS) on depression, anxiety, and neuroticism, we calculated the corresponding PRS of each subject. The results revealed that, among Chinese individuals, the neuroticism PRS could significantly and positively predict both depressive and anxiety symptoms, the depressive symptom PRS could significantly and positively predict anxiety symptoms, and the neuroticism PRS showed the strongest predictive ability.

Study 2 mainly investigates the predictive effects and interactions of individual SES and area SES on depressive and anxiety symptoms. The same sample was used as in Study 1, and 2,090 subjects met the inclusion criteria. Multiple linear regression models were used to perform analyses. The results found that among the various individual SES indicators, the subjective social status (SSS) of the family-of-origin significantly negatively predicted the individual's current depressive and anxiety symptoms, maternal educational level significantly positively predicted the depressive and anxiety symptoms, paternal educational level significantly positively predicted the anxiety symptoms, individual’s current income significantly negatively predicted the depressive symptoms, and individual educational level significantly negatively predicted the depressive and anxiety symptoms. For area SES indicators, the gross domestic product (GDP) per capita, the average years of education and the Townsend deprivation index of the individual’s current long-term living province cannot significantly predict depression or anxiety. However, there were significant interactions between individual SES and area SES. Specifically, high area economic level was protective against depressive symptoms, but this association was only present in individuals with low educational level; in addition, for individuals with high family-oforigin SSS, living in areas with lower educational level significantly reduced their depressive symptoms, which is consistent with the idiom “Better be the head of a dog than the tail of a lion”.

Study 3 intends to investigate how genes and environment work together on depression and anxiety, focusing on analyzing whether PRS interacts with individual SES and area SES. The same sample consisted of 2,090 subjects was used as in Study 2. The PRS variables and SES variables were selected based on the results of Study 1 and Study 2, and multivariate linear regression models were used for analysis. Significant gene-environment interactions were observed: higher family-of-origin SSS predicted lower anxiety symptoms, but this association only existed among individuals with medium or high genetic risk; meanwhile, higher individual educational level also predicted lower anxiety symptoms, but this association was only found in individuals with medium genetic risk.

Overall, this study showed that the depressive symptom PRS and the neuroticism PRS could effectively predict depressive or anxiety symptoms in Chinese individuals; the effects of different SES variables on depressive and anxiety symptoms were different; there were interactions between individual SES and area SES; there were also gene-environment interactions between PRS and family-of-origin SES and current individual SES. The main innovation of this study is that it integrated cutting-edge PRS analysis with individual- and area-level SES to unravel the complex interplay between genetics and environment in depression and anxiety from microscopic genetic molecules level to macroscopic area SES level, and it finally revealed significant geneenvironment interactions and environment-environment interactions. By advancing our comprehension of the mechanisms underlying depression and anxiety, this study provides theoretical insights for formulating mental health prevention, intervention strategies, and public health policies. It also serves as a robust scientific reference for national concerns, including how family-of-origin affects individual mental health, and whether college students should stay in big cities after graduation.