Zandstra Melissa G, Meijs Hannah, Somers Metten, Stam Cornelis J, de Wilde Bieke, van Hecke Jan, Niemegeers Peter, Luykx Jurjen J, van Dellen Edwin
Department of Psychiatry, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands.
Research Institute Brainclinics, Brainclinics Foundation, Nijmegen, Netherlands.
Front Neurosci. 2023 Sep 15;17:1176825. doi: 10.3389/fnins.2023.1176825. eCollection 2023.
Resting-state EEG (rsEEG) characteristics, such as functional connectivity and network topology, are studied as potential biomarkers in psychiatric research. However, the presence of psychopharmacological treatment in study participants poses a potential confounding factor in biomarker research. To address this concern, our study aims to explore the impact of both single and multi-class psychotropic treatments on aforementioned rsEEG characteristics in a psychiatric population.
RsEEG was analyzed in a real-world cross-sectional sample of 900 hospital-admitted psychiatric patients. Patients were clustered into eight psychopharmacological groups: unmedicated, single-class treatment with antipsychotics (AP), antidepressants (AD) or benzodiazepines (BDZ), and multi-class combinations of these treatments. To assess the associations between psychotropic treatments and the macroscale rsEEG characteristics mentioned above, we employed a general linear model with tests. Additionally, Spearman's rank correlation analyses were performed to explore potential dosage effects.
Compared to unmedicated patients, single-class use of AD was associated with lower functional connectivity in the delta band, while AP was associated with lower functional connectivity in both the delta and alpha bands. Single-class use of BDZ was associated with widespread rsEEG differences, including lower functional connectivity across frequency bands and a different network topology within the beta band relative to unmedicated patients. All of the multi-class groups showed associations with functional connectivity or topology measures, but effects were most pronounced for concomitant use of all three classes of psychotropics. Differences were not only observed in comparison with unmedicated patients, but were also evident in comparisons between single-class, multi-class, and single/multi-class groups. Importantly, multi-class associations with rsEEG characteristics were found even in the absence of single-class associations, suggesting potential cumulative or interaction effects of different classes of psychotropics. Dosage correlations were only found for antipsychotics.
Our exploratory, cross-sectional study suggests small but significant associations between single and multi-class use of antidepressants, antipsychotics and benzodiazepines and macroscale rsEEG functional connectivity and network topology characteristics. These findings highlight the importance of considering the effects of specific psychotropics, as well as their interactions, when investigating rsEEG biomarkers in a medicated psychiatric population.
静息态脑电图(rsEEG)特征,如功能连接性和网络拓扑结构,在精神病学研究中作为潜在生物标志物进行研究。然而,研究参与者中存在精神药物治疗在生物标志物研究中构成了一个潜在的混杂因素。为了解决这一问题,我们的研究旨在探讨单类和多类精神药物治疗对精神病患者上述rsEEG特征的影响。
对900名住院精神病患者的真实世界横断面样本进行rsEEG分析。患者被分为八个精神药物治疗组:未用药组、使用抗精神病药物(AP)、抗抑郁药物(AD)或苯二氮䓬类药物(BDZ)的单类治疗组,以及这些治疗的多类组合组。为了评估精神药物治疗与上述宏观rsEEG特征之间的关联,我们采用了带有检验的一般线性模型。此外,进行了斯皮尔曼等级相关分析以探索潜在的剂量效应。
与未用药患者相比,单类使用AD与δ波段功能连接性降低相关,而AP与δ和α波段功能连接性降低相关。单类使用BDZ与广泛的rsEEG差异相关,包括各频段功能连接性降低以及相对于未用药患者β波段内不同的网络拓扑结构。所有多类治疗组均显示与功能连接性或拓扑测量值相关,但所有三类精神药物联合使用时效应最为明显。差异不仅在与未用药患者的比较中观察到,在单类、多类以及单/多类治疗组之间的比较中也很明显。重要的是,即使在不存在单类关联的情况下也发现了多类治疗与rsEEG特征的关联,这表明不同类精神药物可能存在累积或相互作用效应。仅发现抗精神病药物存在剂量相关性。
我们的探索性横断面研究表明,单类和多类使用抗抑郁药、抗精神病药和苯二氮䓬类药物与宏观rsEEG功能连接性和网络拓扑结构特征之间存在微小但显著的关联。这些发现凸显了在有药物治疗的精神病患者群体中研究rsEEG生物标志物时考虑特定精神药物的效应及其相互作用的重要性。