焦虑的脑科学研究与临床应用进展

Advances in anxiety research:Neurocognitive mechanisms and clinical applications

焦虑障碍是我国患病率最高的精神障碍,也是全球第六大致残原因.如何建立精准有效的个体化预防-诊断-治疗体系,成为当前亟须攻克的难题.焦虑障碍主要包括广泛性焦虑障碍(GAD)、惊恐障碍(PD)和社交焦虑障碍(SAD)的亚型;其发病机制和分型机制尚不清楚.本文系统综述了近年来临床焦虑障碍和亚临床焦虑的研究进展,特别是本团队的研究进展,重点从神经认知机制的理论模型和临床应用方面寻求新的见解和研究线索.基于经典认知模型、杏仁核和脑岛中心神经模型,以及静态脑网络模型,我们提出了动态焦虑脑网络模型:强调突显网络、执行控制网络、默认网络和感知网络之间的动态相互作用,这是情绪和认知控制交互作用的基础;网络间的神经振荡负责资源转换和信号同步;去甲肾上腺素系统,特别是蓝斑(LC)-去甲肾上腺素(NE)系统,通过神经递质调节上述过程.本文还总结了焦虑的诊断和预测指标,包括遗传特征、认知特征和神经生物标志物,特别强调了特异频段的神经振荡模式,以及动态脑网络连接,以预测个体化焦虑症状和其他精神疾病.通过在体脑成像、神经环路示踪技术、单细胞组学等技术,全面精准解析焦虑障碍的多维度发病机制,揭示国家一类创新药物GW117抗焦虑分子环路机制及其对机体神经-内分泌-免疫系统的影响,为开发新型抗焦虑药物提供依据;通过采用多模态神经影像、神经生理生化等检测评估手段,筛选和鉴定焦虑障碍预测、识别和早期诊断的客观标记;通过融合多模态脑成像技术和光电磁等神经调控技术,开发个体化精准有效的靶点定位和参数优化方案,筛选和确定焦虑障碍治疗的新型靶标.基于多维度客观标记和新型靶标,在亚临床风险人群和焦虑障碍人群中开展队列研究,构建焦虑障碍人群预测模型,形成焦虑障碍早期预防、精确诊断和有效治疗策略方案.

Recent epidemiological surveys of mental disorders in China indicate increasing public burden with that of anxiety disorders ranking the highest at a lifetime prevalence of 7.57%.Anxiety disorders primarily include subtypes of generalized anxiety disorder(GAD),panic disorder(PD),and social anxiety disorder(SAD);but regardless of practical diagnosis,its general pathogenesis and subtyping mechanisms are unclear.This article systematically reviews recent progress in this research area,especially for our team,focusing on theoretical models of the neurocognitive mechanism and clinical applications for new insights and research clues.Based on the(i)classical cognitive models,(ii)amygdala-and insula-centric neural models,and(iii)statical brain network models,we propose here an updated dynamic brain network model of anxiety and executive function.Specific features of this model are threefold.First,it highlights dynamic interactions among the salience,executive control,default,and perceptual networks,which underlies emotional and cognitive control.Second,neural oscillations among networks are responsible for the resource transformation and signal synchronization.Third,the noradrenergic system,particularly the locus coeruleus(LC)-norepinephrine(NE)system,regulates the above processes through neurotransmitters.The article also summarizes diagnostic and predictive indicators of anxiety disorders,including genetic signatures,cognitive characteristics,and neural biomarkers.In these predictive features,we especially highlight frequency-band-specific neural oscillatory patterns,and connectome-based dynamic brain network connectivity for predictions of personalized anxiety and other psychiatric disorders.They suggest an objective toolset that joins multimodal biomarkers for individualized symptom prediction and monitoring.Associated with these new observations,reviewed interventions and treatment methods in this paper include classical medication and psychological therapy,as well as noninvasive brain stimulations(NBS)of transcranial magnetic stimulation,transcranial direct current stimulation,transcranial alternating current stimulation,transcranial photo biomodulation,and neurofeedback.Though NBS has demonstrated significant therapeutic effects in anxiety and related disorders,specific parameters and protocols are still pending for future improvement.Besides new insights of personalized and targeted precision interventions and graded prevention,we further suggest to identify the neural mechanisms of anxiety across species from rodents and non-human primates,taking advantage of electrophysiology,optogenetics,and in vivo microscopic imaging for modeling common behaviors across species.On the clinical side,we propose to break the traditional classification and diagnosis system that are only based on symptomatology;but instead,to establish a multi-dimensional objective marker system based on the latest Dimensional Approaches to Research Classification and Research Domain Criteria(RDoC).