Research Review: Brain network connectivity and the heterogeneity of depression in adolescence - a precision mental health perspective.

Research Review: Brain network connectivity and the heterogeneity of depression in adolescence - a precision mental health perspective.
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DOI:
10.1111/jcpp.13250
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发表时间:
2020-12
期刊:
Journal of child psychology and psychiatry, and allied disciplines
影响因子:
--
通讯作者:
Guyer AE
Guyer AE
中科院分区:
其他
文献类型:
--
作者:
Chahal R;Gotlib IH;Guyer AE

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青春期是抑郁症发病的高风险时期,其特征在于症状、严重程度和病程的可变性。在青春期,与抑郁症有关的神经回路继续成熟,这表明这是一个重要的干预时期。为了反映最近出现的“精确心理健康”-以人为本的方法来识别,预防和治疗精神病理学-研究人员已经开始记录抑郁症特征的异质性与大脑回路的个体差异之间的关联,最常见的是静息状态功能连接(RSFC)。在这篇综述中,我们提出了新的工作,检查治疗前和治疗后的措施,在抑郁症青少年的网络连接,这些研究揭示了潜在的干预特异性神经标记物的治疗效果。我们还审查了研究结果,研究网络连接和两种类型的抑郁症状和治疗反应之间的关联,在成年人,并指出这项工作可以扩展到抑郁的青少年。最后,我们为研究提供了建议,我们相信这将推动青少年精确心理健康科学的发展。新生研究表明,将基于RSFC的病理生理变化与不同类型的治疗效果和特定干预措施后的情绪变化联系起来,将加强对预后和治疗反应的预测。需要更大样本量和直接比较治疗的研究,以确定RSFC模式是否是抑郁症青少年治疗反应的可靠神经标志物。虽然我们还没有使用RSFC来指导临床决策,但研究RSFC稳定性和可靠性的研究结果表明,基于网络的临床表型分析具有良好的前景。描述抑郁症的具体临床特征之间的对应关系(例如,症状、严重程度和治疗反应)和基于网络的连接模式将有助于开发更有针对性和更有效的方法来评估、预防和治疗青少年抑郁症。
Adolescence is a period of high risk for the onset of depression, characterized by variability in symptoms, severity, and course. During adolescence, the neurocircuitry implicated in depression continues to mature, suggesting that it is an important period for intervention. Reflecting the recent emergence of ‘precision mental health’ – a person-centered approach to identifying, preventing, and treating psychopathology – researchers have begun to document associations between heterogeneity in features of depression and individual differences in brain circuitry, most frequently in resting-state functional connectivity (RSFC). In this review, we present emerging work examining pre- and post-treatment measures of network connectivity in depressed adolescents; these studies reveal potential intervention-specific neural markers of treatment efficacy. We also review findings from studies examining associations between network connectivity and both types of depressive symptoms and response to treatment in adults, and indicate how this work can be extended to depressed adolescents. Finally, we offer recommendations for research that we believe will advance the science of precision mental health of adolescence. Nascent studies suggest that linking RSFC-based pathophysiological variation with effects of different types of treatment and changes in mood following specific interventions will strengthen predictions of prognosis and treatment response. Studies with larger sample sizes and direct comparisons of treatments are required to determine whether RSFC patterns are reliable neuromarkers of treatment response for depressed adolescents. Although we are not yet at the point of using RSFC to guide clinical decision-making, findings from research examining the stability and reliability of RSFC point to a favorable future for network-based clinical phenotyping. Delineating the correspondence between specific clinical characteristics of depression (e.g., symptoms, severity, and treatment response) and patterns of network-based connectivity will facilitate the development of more tailored and effective approaches to the assessment, prevention, and treatment of depression in adolescents.
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