Predicting Antidepressant Citalopram Treatment Response via Changes in Brain Functional Connectivity After Acute Intravenous Challenge.
Predicting Antidepressant Citalopram Treatment Response via Changes in Brain Functional Connectivity After Acute Intravenous Challenge.
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DOI：
10.3389/fncom.2020.554186
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发表时间：
2020
影响因子：
3.2
通讯作者：
Lanzenberger R
中科院分区：
文献类型：
--
作者：
Klöbl M;Gryglewski G;Rischka L;Godbersen GM;Unterholzner J;Reed MB;Michenthaler P;Vanicek T;Winkler-Pjrek E;Hahn A;Kasper S;Lanzenberger R
简介：早期和治疗特定的预测治疗成功的重性抑郁症是至关重要的，由于高终身患病率，和异质性的反应标准药物和症状的表达。因此，本研究基于西酞普兰对功能连接的短期影响评估了艾司西酞普兰长期抗抑郁作用的可预测性。研究方法：29名患有重性抑郁症的受试者在静脉注射西酞普兰和安慰剂的影响下，以随机、双盲、交叉的方式，用静息态功能磁共振成像扫描两次。在艾司西酞普兰治疗前后（中位数为7周）采用汉密尔顿抑郁量表（HAM-D）和贝克抑郁量表（BDI）确定症状因素。从全脑功能连接计算预测因子，输入稳健的回归模型，并进行交叉验证。结果：HAM-D中失眠的1个因子对失眠总分有显著的预测力（r = 0.45-0.55）。缓解和响应，可以进一步预测与0.73和0.68的受试者工作特征曲线下的面积分别。功能区的预测具有较高的影响力，特别是位于腹侧注意，额顶叶，和默认模式网络。结论：研究表明，可以使用急性药理学激发期间测量的功能连接作为易于评估的成像标志物来预测药物特异性抗抑郁症状改善。具有高影响力的区域以前与重性抑郁症以及对选择性5-羟色胺再摄取抑制剂的反应有关，证实了目前专注于治疗特异性症状改善的方法的优势。
Introduction: The early and therapy-specific prediction of treatment success in major depressive disorder is of paramount importance due to high lifetime prevalence, and heterogeneity of response to standard medication and symptom expression. Hence, this study assessed the predictability of long-term antidepressant effects of escitalopram based on the short-term influence of citalopram on functional connectivity. Methods: Twenty nine subjects suffering from major depression were scanned twice with resting-state functional magnetic resonance imaging under the influence of intravenous citalopram and placebo in a randomized, double-blinded cross-over fashion. Symptom factors were identified for the Hamilton depression rating scale (HAM-D) and Beck's depression inventory (BDI) taken before and after a median of seven weeks of escitalopram therapy. Predictors were calculated from whole-brain functional connectivity, fed into robust regression models, and cross-validated. Results: Significant predictive power could be demonstrated for one HAM-D factor describing insomnia and the total score (r = 0.45–0.55). Remission and response could furthermore be predicted with an area under the receiver operating characteristic curve of 0.73 and 0.68, respectively. Functional regions with high influence on the predictor were located especially in the ventral attention, fronto-parietal, and default mode networks. Conclusion: It was shown that medication-specific antidepressant symptom improvements can be predicted using functional connectivity measured during acute pharmacological challenge as an easily assessable imaging marker. The regions with high influence have previously been related to major depression as well as the response to selective serotonin reuptake inhibitors, corroborating the advantages of the current approach of focusing on treatment-specific symptom improvements.
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DOI：
10.1016/j.pnpbp.2018.01.021
发表时间：
2018-06-08
影响因子：
5.6
作者：
Arnone D;Wise T;Walker C;Cowen PJ;Howes O;Selvaraj S
通讯作者：
Selvaraj S
影响因子：
6.8
作者：
Argyelan M;Lencz T;Kaliora S;Sarpal DK;Weissman N;Kingsley PB;Malhotra AK;Petrides G
通讯作者：
Petrides G
影响因子：
82.9
作者：
Drysdale AT;Grosenick L;Downar J;Dunlop K;Mansouri F;Meng Y;Fetcho RN;Zebley B;Oathes DJ;Etkin A;Schatzberg AF;Sudheimer K;Keller J;Mayberg HS;Gunning FM;Alexopoulos GS;Fox MD;Pascual-Leone A;Voss HU;Casey BJ;Dubin MJ;Liston C
通讯作者：
Liston C
影响因子：
29.9
作者：
Fonzo, Gregory A.;Etkin, Amit;Trivedi, Madhukar H.
通讯作者：
Trivedi, Madhukar H.
影响因子：
6.1
作者：
Burke, WJ
通讯作者：
Burke, WJ