• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

通过使用速效抗抑郁药在情绪障碍研究中开发生物标志物。

Developing biomarkers in mood disorders research through the use of rapid-acting antidepressants.

作者信息

Niciu Mark J, Mathews Daniel C, Nugent Allison C, Ionescu Dawn F, Furey Maura L, Richards Erica M, Machado-Vieira Rodrigo, Zarate Carlos A

机构信息

Experimental Therapeutics & Pathophysiology Branch, Intramural Research Program, National Institute of Mental Health, National Institutes of Health, and Department of Health and Human Services, Bethesda, Maryland.

出版信息

Depress Anxiety. 2014 Apr;31(4):297-307. doi: 10.1002/da.22224. Epub 2013 Dec 18.

DOI:10.1002/da.22224
PMID:24353110
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3984598/
Abstract

An impediment to progress in mood disorders research is the lack of analytically valid and qualified diagnostic and treatment biomarkers. Consistent with the National Institute of Mental Health (NIMH)'s Research Domain Criteria (RDoC) initiative, the lack of diagnostic biomarkers has precluded us from moving away from a purely subjective (symptom-based) toward a more objective diagnostic system. In addition, treatment response biomarkers in mood disorders would facilitate drug development and move beyond trial-and-error toward more personalized treatments. As such, biomarkers identified early in the pathophysiological process are proximal biomarkers (target engagement), while those occurring later in the disease process are distal (disease pathway components). One strategy to achieve this goal in biomarker development is to increase efforts at the initial phases of biomarker development (i.e. exploration and validation) at single sites with the capability of integrating multimodal approaches across a biological systems level. Subsequently, resultant putative biomarkers could then undergo characterization and surrogacy as these latter phases require multisite collaborative efforts. We have used multimodal approaches - genetics, proteomics/metabolomics, peripheral measures, multimodal neuroimaging, neuropsychopharmacological challenge paradigms and clinical predictors - to explore potential predictor and mediator/moderator biomarkers of the rapid-acting antidepressants ketamine and scopolamine. These exploratory biomarkers may then be used for a priori stratification in larger multisite controlled studies during the validation and characterization phases with the ultimate goal of surrogacy. In sum, the combination of target engagement and well-qualified disease-related measures are crucial to improve our pathophysiological understanding, personalize treatment selection, and expand our armamentarium of novel therapeutics.

摘要

情绪障碍研究进展的一个阻碍是缺乏分析上有效且合格的诊断和治疗生物标志物。与美国国立精神卫生研究所(NIMH)的研究领域标准(RDoC)计划一致,诊断生物标志物的缺乏使我们无法从纯粹主观的(基于症状的)诊断系统转向更客观的诊断系统。此外,情绪障碍的治疗反应生物标志物将促进药物开发,并从试错法转向更个性化的治疗。因此,在病理生理过程早期识别出的生物标志物是近端生物标志物(靶点参与),而在疾病过程后期出现的生物标志物是远端生物标志物(疾病途径成分)。在生物标志物开发中实现这一目标的一种策略是,在能够整合生物系统水平多模态方法的单一研究点,加大生物标志物开发初始阶段(即探索和验证)的力度。随后,由于后期阶段需要多中心合作,由此产生的假定生物标志物可进行特征描述和替代验证。我们使用了多模态方法——遗传学、蛋白质组学/代谢组学、外周测量、多模态神经影像学、神经精神药理学激发范式和临床预测指标——来探索快速起效的抗抑郁药氯胺酮和东莨菪碱的潜在预测指标以及中介/调节生物标志物。这些探索性生物标志物随后可在验证和特征描述阶段用于更大规模的多中心对照研究中的先验分层,最终目标是进行替代验证。总之,靶点参与和合格的疾病相关测量指标的结合对于提高我们对病理生理学的理解、个性化治疗选择以及扩大我们的新型治疗手段至关重要。

相似文献

1
Developing biomarkers in mood disorders research through the use of rapid-acting antidepressants.通过使用速效抗抑郁药在情绪障碍研究中开发生物标志物。
Depress Anxiety. 2014 Apr;31(4):297-307. doi: 10.1002/da.22224. Epub 2013 Dec 18.
2
Biomarkers in mood disorders research: developing new and improved therapeutics.情绪障碍研究中的生物标志物:开发新的和改进的治疗方法。
Rev Psiquiatr Clin. 2014;41(5):131-134. doi: 10.1590/0101-60830000000027.
3
Human biomarkers of rapid antidepressant effects.快速抗抑郁作用的人类生物标志物。
Biol Psychiatry. 2013 Jun 15;73(12):1142-55. doi: 10.1016/j.biopsych.2012.11.031. Epub 2013 Jan 29.
4
Letter to the Editor: CONVERGENCES AND DIVERGENCES IN THE ICD-11 VS. DSM-5 CLASSIFICATION OF MOOD DISORDERS.给编辑的信:《ICD-11 与 DSM-5 心境障碍分类的趋同与分歧》
Turk Psikiyatri Derg. 2021;32(4):293-295. doi: 10.5080/u26899.
5
Affective disorder and epilepsy comorbidity: implications for development of treatments, preventions and diagnostic approaches.情感障碍与癫痫共病:对治疗、预防和诊断方法发展的影响。
Clin EEG Neurosci. 2004 Jan;35(1):53-68. doi: 10.1177/155005940403500112.
6
Precision medicine for suicidality: from universality to subtypes and personalization.自杀倾向的精准医学:从普遍性到亚型及个性化
Mol Psychiatry. 2017 Sep;22(9):1250-1273. doi: 10.1038/mp.2017.128. Epub 2017 Aug 15.
7
[Biomarkers for Mood Disorders and a Novel Antidepressant (R)-ketamine].[情绪障碍的生物标志物与一种新型抗抑郁药(R)-氯胺酮]
Brain Nerve. 2017 Oct;69(10):1143-1148. doi: 10.11477/mf.1416200882.
8
Updates on Preclinical and Translational Neuroscience of Mood Disorders: A Brief Historical Focus on Ketamine for the Clinician.心境障碍的临床前和转化神经科学研究进展:氯胺酮治疗心境障碍的简要历史回顾
J Clin Psychopharmacol. 2019 Nov/Dec;39(6):665-672. doi: 10.1097/JCP.0000000000001132.
9
Developing a clinical translational neuroscience taxonomy for anxiety and mood disorder: protocol for the baseline-follow up Research domain criteria Anxiety and Depression ("RAD") project.开发用于焦虑和情绪障碍的临床转化神经科学分类法:基线-随访研究领域标准焦虑与抑郁(“RAD”)项目方案。
BMC Psychiatry. 2016 Mar 15;16:68. doi: 10.1186/s12888-016-0771-3.
10
Cholinergic regulation of mood: from basic and clinical studies to emerging therapeutics.胆碱能调节情绪:从基础和临床研究到新兴治疗方法。
Mol Psychiatry. 2019 May;24(5):694-709. doi: 10.1038/s41380-018-0219-x. Epub 2018 Aug 17.

引用本文的文献

1
Exploring the ElectroRetinoGraphy as a biomarker for predicting and monitoring therapeutic response to antidepressants in major depressive disorder: study protocol for the MESANTIDEP trial.探索视网膜电图作为预测和监测重度抑郁症患者对抗抑郁药治疗反应的生物标志物:MESANTIDEP试验的研究方案
Front Psychiatry. 2025 Apr 25;16:1501166. doi: 10.3389/fpsyt.2025.1501166. eCollection 2025.
2
Portable light therapy in the treatment of unipolar non-seasonal major depressive disorder: study protocol for the LUMIDEP randomised controlled trial.便携式光疗治疗单相非季节性重性抑郁障碍:LUMIDEP 随机对照试验研究方案。
BMJ Open. 2021 Jul 9;11(7):e049331. doi: 10.1136/bmjopen-2021-049331.
3

本文引用的文献

1
Mood stabilizer treatment increases serotonin type 1A receptor binding in bipolar depression.心境稳定剂治疗可增加双相抑郁患者 5-羟色胺 1A 受体结合。
J Psychopharmacol. 2013 Oct;27(10):894-902. doi: 10.1177/0269881113499204. Epub 2013 Aug 7.
2
Fluid biomarkers in Alzheimer's disease - current concepts.阿尔茨海默病的液体生物标志物——当前概念。
Mol Neurodegener. 2013 Jun 21;8:20. doi: 10.1186/1750-1326-8-20.
3
Neuroimaging in psychiatric pharmacogenetics research: the promise and pitfalls.神经影像学在精神药理学遗传学研究中的应用:前景与挑战。
New Methods for Assessing Rapid Changes in Suicide Risk.
评估自杀风险快速变化的新方法。
Front Psychiatry. 2021 Jan 26;12:598434. doi: 10.3389/fpsyt.2021.598434. eCollection 2021.
4
Neuroimaging Biomarkers for Predicting Treatment Response and Recurrence of Major Depressive Disorder.神经影像学生物标志物可预测重度抑郁症的治疗反应和复发。
Int J Mol Sci. 2020 Mar 20;21(6):2148. doi: 10.3390/ijms21062148.
5
Bayesian adaptive randomization trial of intravenous ketamine for veterans with late-life, treatment-resistant depression.静脉注射氯胺酮治疗老年难治性抑郁症退伍军人的贝叶斯适应性随机试验
Contemp Clin Trials Commun. 2019 Aug 21;16:100432. doi: 10.1016/j.conctc.2019.100432. eCollection 2019 Dec.
6
Leveraging Machine Learning Approaches for Predicting Antidepressant Treatment Response Using Electroencephalography (EEG) and Clinical Data.利用机器学习方法结合脑电图(EEG)和临床数据预测抗抑郁治疗反应
Front Psychiatry. 2019 Jan 14;9:768. doi: 10.3389/fpsyt.2018.00768. eCollection 2018.
7
Recognition and Treatment of Cognitive Dysfunction in Major Depressive Disorder.重度抑郁症认知功能障碍的识别与治疗
Front Psychiatry. 2018 Dec 4;9:655. doi: 10.3389/fpsyt.2018.00655. eCollection 2018.
8
Exploratory genome-wide association analysis of response to ketamine and a polygenic analysis of response to scopolamine in depression.抑郁症患者对氯胺酮和东莨菪碱反应的探索性全基因组关联分析。
Transl Psychiatry. 2018 Dec 14;8(1):280. doi: 10.1038/s41398-018-0311-7.
9
Cross-species examination of single- and multi-strain probiotic treatment effects on neuropsychiatric outcomes.跨物种研究单一和多菌株益生菌治疗对神经精神结局的影响。
Neurosci Biobehav Rev. 2019 Apr;99:160-197. doi: 10.1016/j.neubiorev.2018.11.010. Epub 2018 Nov 22.
10
Neurophysiological Changes Associated with Antidepressant Response to Ketamine Not Observed in a Negative Trial of Scopolamine in Major Depressive Disorder.与抗抑郁药氯胺酮反应相关的神经生理变化在一项大 抑郁症中莨菪碱阴性试验中未观察到。
Int J Neuropsychopharmacol. 2019 Jan 1;22(1):10-18. doi: 10.1093/ijnp/pyy051.
Neuropsychopharmacology. 2013 Nov;38(12):2327-37. doi: 10.1038/npp.2013.152. Epub 2013 Jun 24.
4
Scopolamine rapidly increases mammalian target of rapamycin complex 1 signaling, synaptogenesis, and antidepressant behavioral responses.东莨菪碱可迅速增强哺乳动物雷帕霉素靶蛋白复合物 1 信号、突触形成和抗抑郁行为反应。
Biol Psychiatry. 2013 Nov 15;74(10):742-9. doi: 10.1016/j.biopsych.2013.04.025. Epub 2013 Jun 14.
5
Human biomarkers of rapid antidepressant effects.快速抗抑郁作用的人类生物标志物。
Biol Psychiatry. 2013 Jun 15;73(12):1142-55. doi: 10.1016/j.biopsych.2012.11.031. Epub 2013 Jan 29.
6
2012 FDA drug approvals.2012年美国食品药品监督管理局批准的药物
Nat Rev Drug Discov. 2013 Feb;12(2):87-90. doi: 10.1038/nrd3946.
7
Potential of pretreatment neural activity in the visual cortex during emotional processing to predict treatment response to scopolamine in major depressive disorder.视觉皮层情绪处理过程中的预处理神经活动对预测大 抑郁症患者东莨菪碱治疗反应的潜力。
JAMA Psychiatry. 2013 Mar;70(3):280-90. doi: 10.1001/2013.jamapsychiatry.60.
8
Toward a systems biology of mood disorder.迈向情绪障碍的系统生物学。
Biol Psychiatry. 2013 Jan 15;73(2):107-8. doi: 10.1016/j.biopsych.2012.10.009.
9
NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia.NMDA 受体在大规模负相关神经网络系统中的功能及其对认知和精神分裂症的影响。
Proc Natl Acad Sci U S A. 2012 Oct 9;109(41):16720-5. doi: 10.1073/pnas.1208494109. Epub 2012 Sep 25.
10
Quantitative proteomic approaches in biomarker discovery of inflammatory bowel disease.炎症性肠病生物标志物发现的定量蛋白质组学方法。
J Dig Dis. 2012 Oct;13(10):497-503. doi: 10.1111/j.1751-2980.2012.00625.x.