Stress Markers for Mental States and Biotypes of Depression and Anxiety: A Scoping Review and Preliminary Illustrative Analysis.

Q1 Psychology Chronic Stress Pub Date : 2021-04-22 eCollection Date: 2021-01-01 DOI:10.1177/24705470211000338
Megan Chesnut, Sahar Harati, Pablo Paredes, Yasser Khan, Amir Foudeh, Jayoung Kim, Zhenan Bao, Leanne M Williams
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Abstract

Depression and anxiety disrupt daily function and their effects can be long-lasting and devastating, yet there are no established physiological indicators that can be used to predict onset, diagnose, or target treatments. In this review, we conceptualize depression and anxiety as maladaptive responses to repetitive stress. We provide an overview of the role of chronic stress in depression and anxiety and a review of current knowledge on objective stress indicators of depression and anxiety. We focused on cortisol, heart rate variability and skin conductance that have been well studied in depression and anxiety and implicated in clinical emotional states. A targeted PubMed search was undertaken prioritizing meta-analyses that have linked depression and anxiety to cortisol, heart rate variability and skin conductance. Consistent findings include reduced heart rate variability across depression and anxiety, reduced tonic and phasic skin conductance in depression, and elevated cortisol at different times of day and across the day in depression. We then provide a brief overview of neural circuit disruptions that characterize particular types of depression and anxiety. We also include an illustrative analysis using predictive models to determine how stress markers contribute to specific subgroups of symptoms and how neural circuits add meaningfully to this prediction. For this, we implemented a tree-based multi-class classification model with physiological markers of heart rate variability as predictors and four symptom subtypes, including normative mood, as target variables. We achieved 40% accuracy on the validation set. We then added the neural circuit measures into our predictor set to identify the combination of neural circuit dysfunctions and physiological markers that accurately predict each symptom subtype. Achieving 54% accuracy suggested a strong relationship between those neural-physiological predictors and the mental states that characterize each subtype. Further work to elucidate the complex relationships between physiological markers, neural circuit dysfunction and resulting symptoms would advance our understanding of the pathophysiological pathways underlying depression and anxiety.

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抑郁和焦虑的精神状态和生物类型的压力标记:范围审查和初步说明性分析》。
抑郁和焦虑会扰乱人的日常功能,其影响可能是持久的、破坏性的,但目前还没有成熟的生理指标可用于预测发病、诊断或有针对性的治疗。在本综述中,我们将抑郁和焦虑概念化为对重复性压力的适应不良反应。我们概述了慢性压力在抑郁症和焦虑症中的作用,并回顾了目前有关抑郁症和焦虑症客观压力指标的知识。我们重点研究了皮质醇、心率变异性和皮肤传导性,这些指标在抑郁和焦虑症中得到了充分的研究,并与临床情绪状态有关。我们在 PubMed 上进行了有针对性的搜索,优先考虑将抑郁和焦虑与皮质醇、心率变异性和皮肤传导性联系起来的荟萃分析。一致的研究结果包括抑郁症和焦虑症患者的心率变异性降低,抑郁症患者的强直性和相位性皮肤传导性降低,以及抑郁症患者皮质醇在一天中不同时间段和全天范围内升高。然后,我们简要概述了特定类型抑郁症和焦虑症的神经回路紊乱特征。我们还利用预测模型进行了说明性分析,以确定压力标记物是如何导致特定亚组症状的,以及神经回路是如何为这一预测带来意义的。为此,我们实施了一个基于树的多类分类模型,将心率变异性的生理标记作为预测因子,将包括正常情绪在内的四种症状亚型作为目标变量。我们在验证集上取得了 40% 的准确率。然后,我们将神经回路测量值加入预测集,以确定神经回路功能障碍和生理标记的组合,从而准确预测每种症状亚型。54% 的准确率表明,这些神经生理预测因子与每种亚型的心理状态之间都存在密切关系。进一步阐明生理标记、神经回路功能障碍和由此产生的症状之间的复杂关系,将有助于我们了解抑郁和焦虑的病理生理途径。
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来源期刊
Chronic Stress
Chronic Stress Psychology-Clinical Psychology
CiteScore
7.40
自引率
0.00%
发文量
25
审稿时长
6 weeks
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