庞庞 (2023-03-31 15:06):
#paper https://doi.org/10.1038/s41380-023-01958-8 Individualized fMRI connectivity defines signatures of antidepressant and placebo responses in major depression 由于个体的异质性,不同个体对抗抑郁药物的缓释程度各有不同。因此,理解抗抑郁药物的作用机制对个性化医疗至关重要。本文采用去除组成分的COBE算法,获得个体化的功能连接矩阵,作为特征对抗抑郁药物舍曲林和安慰剂的疗效进行预测。研究发现,个体化的功能连接比起组水平的功能连接显著提高了预测准确率;对预测舍曲林贡献高的脑区主要位于左侧颞中皮层和右侧脑岛;对安慰剂贡献高的主要位于双侧扣带皮层和左侧颞上皮层。这位抗抑郁的疗效预测标志物提供了新视角。
IF:9.600Q1 Molecular psychiatry, 2023-06. DOI: 10.1038/s41380-023-01958-8 PMID: 36732585
Individualized fMRI connectivity defines signatures of antidepressant and placebo responses in major depression
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Abstract:
Though sertraline is commonly prescribed in patients with major depressive disorder (MDD), its superiority over placebo is only marginal. This is in part due to the neurobiological heterogeneity of the individuals. Characterizing individual-unique functional architecture of the brain may help better dissect the heterogeneity, thereby defining treatment-predictive signatures to guide personalized medication. In this study, we investigate whether individualized brain functional connectivity (FC) can define more predictable signatures of antidepressant and placebo treatment in MDD. The data used in the present work were collected by the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study. Patients (N = 296) were randomly assigned to antidepressant sertraline or placebo double-blind treatment for 8 weeks. The whole-brain FC networks were constructed from pre-treatment resting-state functional magnetic resonance imaging (rs-fMRI). Then, FC was individualized by removing the common components extracted from the raw baseline FC to train regression-based connectivity predictive models. With individualized FC features, the established prediction models successfully identified signatures that explained 22% variance for the sertraline group and 31% variance for the placebo group in predicting HAMD change. Compared with the raw FC-based models, the individualized FC-defined signatures significantly improved the prediction performance, as confirmed by cross-validation. For sertraline treatment, predictive FC metrics were predominantly located in the left middle temporal cortex and right insula. For placebo, predictive FC metrics were primarily located in the bilateral cingulate cortex and left superior temporal cortex. Our findings demonstrated that through the removal of common FC components, individualization of FC metrics enhanced the prediction performance compared to raw FC. Associated with previous MDD clinical studies, our identified predictive biomarkers provided new insights into the neuropathology of antidepressant and placebo treatment.
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