Arias-Magnasco Angelo, Lin Bochao Danae, Pries Lotta-Katrin, Guloksuz Sinan
Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht University Medical Centre, Maastricht, The Netherlands.
Department of Preventive Medicine, Institute of Biomedical Informatics, Bioinformatics Center, School of Basic Medical Sciences, Henan University, Kaifeng, China.
Psychol Med. 2025 Feb 7;55:e16. doi: 10.1017/S0033291724003015.
Dissecting the exposome linked to mental health outcomes can help identify potentially modifiable targets to improve mental well-being. However, the multiplicity of exposures and the complexity of mental health phenotypes pose a challenge that requires data-driven approaches.
Guided by our previous systematic approach, we conducted hypothesis-free exposome-wide analyses to identify factors associated with 7 psychiatric diagnostic domains and 19 symptom dimensions in 157,298 participants from the UK Biobank Mental Health Survey. After quality control, 294 environmental, lifestyle, behavioral, and economic variables were included. An Exposome-Wide Association Study was conducted per outcome in two equally split datasets. Variables associated with each outcome were then tested in a multivariable model.
Across all diagnostic domains and symptom dimensions, the top three exposures were childhood adversities and traumatic events. Cannabis use was associated with common psychiatric disorders (depressive, anxiety, psychotic, and bipolar manic disorders), with ORs ranging from 1.10 to 1.79 in the multivariable models. Additionally, differential associations were identified between specific outcomes-such as neurodevelopmental disorders, eating disorders, and self-harm behaviors-and exposures, including early life experiences (being adopted), lifestyle (time spent using computers), and dietary habits (vegetarian diet).
This comprehensive mapping of the exposome revealed that several factors, particularly in the domains of those previously well-studied were shared across mental health phenotypes, providing further support for transdiagnostic pathoetiology. Our findings also showed that distinct relations might exist. Continued exposome research through multimodal mechanistic studies guided by the transdiagnostic mental health framework is required to better inform public health policies.
剖析与心理健康结果相关的暴露组有助于识别潜在的可改变目标,以改善心理健康。然而,暴露因素的多样性和心理健康表型的复杂性带来了挑战,需要采用数据驱动的方法。
在我们之前的系统方法指导下,我们进行了无假设的全暴露组分析,以确定来自英国生物银行心理健康调查的157298名参与者中与7个精神疾病诊断领域和19个症状维度相关的因素。经过质量控制后,纳入了294个环境、生活方式、行为和经济变量。在两个均等分割的数据集中,针对每个结果进行了全暴露组关联研究。然后在多变量模型中对与每个结果相关的变量进行测试。
在所有诊断领域和症状维度中,排名前三的暴露因素是童年逆境和创伤事件。使用大麻与常见精神疾病(抑郁、焦虑、精神病和双相躁狂症)相关,在多变量模型中,比值比范围为1.10至1.79。此外,还确定了特定结果(如神经发育障碍、饮食失调和自伤行为)与暴露因素(包括早年经历(被收养)、生活方式(使用电脑的时间)和饮食习惯(素食))之间的差异关联。
对暴露组的这种全面映射表明,几个因素,特别是在那些先前已充分研究的领域中的因素,在心理健康表型中是共有的,为跨诊断病理病因学提供了进一步支持。我们的数据还表明可能存在独特的关系。需要通过以跨诊断心理健康框架为指导的多模式机制研究继续进行暴露组研究,以便为公共卫生政策提供更好的信息。