Data_Sheet_1_Associations between psychotropic drugs and rsEEG connectivity and network characteristics: a cross-sectional study in hospital-admitted psychiatric patients.pdf

IntroductionResting-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.
MethodsRsEEG 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 post-hoc tests. Additionally, Spearman’s rank correlation analyses were performed to explore potential dosage effects.
ResultsCompared 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.
ConclusionOur 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.

引言：静息态脑电图（resting-state EEG, rsEEG）特征（如功能连接与网络拓扑）作为潜在生物标志物被应用于精神病学研究。然而，研究受试者所接受的精神药物治疗可能为生物标志物研究带来潜在混杂偏倚。为解决这一问题，本研究旨在探究单类别与多类别精神药物治疗对精神病患者群体中上述rsEEG特征的影响。
方法：本研究对900名住院精神病患者的真实世界横断面样本进行了rsEEG分析。将患者划分为8个精神药物治疗组别：未用药组、仅接受抗精神病药（antipsychotics, AP）、抗抑郁药（antidepressants, AD）或苯二氮䓬类药物（benzodiazepines, BDZ）的单类别治疗组，以及上述药物的多类别联合治疗组。为评估精神药物治疗与上述宏观尺度rsEEG特征之间的关联，本研究采用了广义线性模型结合事后检验方法。此外，还通过斯皮尔曼等级相关分析探究了潜在的剂量效应。
结果：与未用药患者相比，仅使用抗抑郁药的患者δ频段功能连接水平更低，而仅使用抗精神病药的患者δ与α频段功能连接水平均更低。仅使用苯二氮䓬类药物的患者存在广泛的rsEEG差异，包括全频段功能连接降低，以及相较于未用药患者β频段的网络拓扑结构发生改变。所有多类别治疗组均表现出与功能连接或拓扑测量指标的关联，其中同时使用三类精神药物的组别效应最为显著。差异不仅体现在与未用药组的比较中，在单类别治疗组、多类别治疗组以及单/多类别治疗组之间的比较中同样显著。值得注意的是，即使在单类别治疗未表现出关联的情况下，仍观察到多类别治疗与rsEEG特征的关联，这提示不同类别精神药物可能存在累积效应或交互效应。仅在抗精神病药中发现了剂量相关性。
结论：本探索性横断面研究表明，抗抑郁药、抗精神病药与苯二氮䓬类药物的单类别与多类别使用，与宏观尺度rsEEG的功能连接及网络拓扑特征存在微弱但显著的关联。上述研究结果凸显了在针对用药精神病患者群体开展rsEEG生物标志物研究时，需考虑特定精神药物的效应及其相互作用的重要性。