Chilver Miranda R, Keller Arielle S, Park Haeme R P, Jamshidi Javad, Montalto Arthur, Schofield Peter R, Clark C Richard, Harmon-Jones Eddie, Williams Leanne M, Gatt Justine M
Neuroscience Research Australia, Randwick, New South Wales, 2031, Australia; School of Psychology, University of New South Wales, Sydney, New South Wales, 2052, Australia.
Department of Psychiatry and Behavioral Sciences, Stanford School of Medicine, Stanford University, Stanford, CA, 94305-5717, USA.
J Psychiatr Res. 2020 Jul;126:114-121. doi: 10.1016/j.jpsychires.2020.04.010. Epub 2020 May 8.
Alterations to electroencephalography (EEG) power have been reported for psychiatric conditions such as depression and anxiety, but not for mental wellbeing in a healthy population. This study examined the resting EEG profiles associated with mental wellbeing, and how genetics and environment contribute to these associations using twin modelling. Mental wellbeing was assessed using the COMPAS-W Wellbeing Scale which measures both subjective and psychological wellbeing. In 422 healthy adult monozygotic and dizygotic twins aged 18-61 years, we examined the association between mental wellbeing and EEG power (alpha, beta, theta, delta) using linear mixed models. This was followed by univariate and multivariate twin modelling to assess the heritability of wellbeing and EEG power, and whether the association was driven by shared genetics or environment. A significant association between wellbeing and an interaction of alpha, beta, and delta (ABD) power was found (β = -0.33, p < 0.001) whereby a profile of high alpha and delta and low beta was associated with higher wellbeing, independent of depression and anxiety symptoms. This finding was supported by a five-fold cross-validation analysis. A significant genetic correlation (rG = -0.43) was found to account for 94% of the association between wellbeing and the EEG power interaction. Together, this study has identified a novel EEG profile with a common genetic component that may be a potential biomarker of mental wellbeing. Future studies need to clarify the causal direction of this association.
已有研究报道，诸如抑郁症和焦虑症等精神疾病会导致脑电图（EEG）功率改变，但健康人群的心理健康状况与EEG功率之间的关系尚未见报道。本研究通过双胞胎模型，研究了与心理健康相关的静息EEG特征，以及基因和环境如何影响这些特征。使用COMPAS-W幸福感量表评估心理健康状况，该量表同时测量主观幸福感和心理幸福感。在422名年龄在18-61岁之间的健康成年同卵和异卵双胞胎中，我们使用线性混合模型研究了心理健康与EEG功率（α、β、θ、δ）之间的关系。随后进行单变量和多变量双胞胎模型分析，以评估幸福感和EEG功率的遗传性，以及这种关联是由共享基因还是环境驱动的。研究发现，幸福感与α、β和δ（ABD）功率的相互作用之间存在显著关联（β = -0.33，p < 0.001），即高α和δ以及低β的特征与更高程度的幸福感相关，且与抑郁和焦虑症状无关。这一发现得到了五重交叉验证分析的支持。研究发现，显著的遗传相关性（rG = -0.43）占幸福感与EEG功率相互作用之间关联的94%。总之，本研究确定了一种具有共同遗传成分的新型EEG特征，这可能是心理健康的潜在生物标志物。未来的研究需要阐明这种关联的因果方向。
