Biomarkers to Predict Antidepressant Response

被引：115

作者：

Leuchter, Andrew F. ^{[1
,2
]}

Cook, Ian A. ^{[1
,2
]}

Hamilton, Steven P. ^{[3
,4
]}

Narr, Katherine L. ^{[5
]}

Toga, Arthur ^{[5
]}

Hunter, Aimee M. ^{[1
,2
]}

Faull, Kym ^{[2
,6
]}

Whitelegge, Julian ^{[2
,6
]}

Andrews, Anne M. ^{[2
]}

Loo, Joseph

Way, Baldwin ^{[7
]}

Nelson, Stanley F. ^{[2
,8
]}

Horvath, Steven ^{[8
,9
]}

Lebowitz, Barry D. ^{[10
]}

机构：

[1] Univ Calif Los Angeles, Semel Inst Neurosci & Human Behav, David Geffen Sch Med, Lab Brain Behav & Pharmacol, Los Angeles, CA 90024 USA

[2] Univ Calif Los Angeles, Semel Inst Neurosci & Human Behav, David Geffen Sch Med, Dept Psychiat & Biobehav Sci, Los Angeles, CA 90024 USA

[3] Univ Calif San Francisco, Dept Psychiat, San Francisco, CA 94143 USA

[4] Univ Calif San Francisco, Inst Human Genet, San Francisco, CA 94143 USA

[5] Univ Calif Los Angeles, David Geffen Sch Med, Dept Neurol, Lab Neuro Imaging, Los Angeles, CA 90024 USA

[6] Univ Calif Los Angeles, David Geffen Sch Med, Dept Chem & Biochem, Pasarow Mass Spectrometry Lab, Los Angeles, CA 90024 USA

[7] Univ Calif Los Angeles, Dept Psychol, Social Cognit Neurosci Lab, Los Angeles, CA 90024 USA

[8] Univ Calif Los Angeles, David Geffen Sch Med, Dept Human Genet, Los Angeles, CA 90024 USA

[9] Univ Calif Los Angeles, Sch Publ Hlth, Dept Biostat, Los Angeles, CA 90024 USA

[10] UCSD Sch Med, Dept Psychiat, Sam & Rose Stein Inst Res Aging, San Diego, CA USA

来源：

CURRENT PSYCHIATRY REPORTS | 2010年 / 12卷 / 06期

基金：

美国国家卫生研究院;

关键词：

Biomarkers; Major depression; Predicting treatment response; Brain imaging; Magnetic resonance imaging (MRI); Quantitative electroencephalography (QEEG); Cordance; Antidepressant Treatment Response (ATR) Index; Positron emission tomography (PET); Pharmacogenomics; Proteomics; Metabolomics; STAR-ASTERISK-D; MOOD-REGULATING CIRCUIT; ANTERIOR CINGULATE CORTEX; UNIPOLAR MAJOR DEPRESSION; SEROTONIN TRANSPORTER; HIPPOCAMPAL VOLUME; FACIAL EXPRESSIONS; NEURAL RESPONSE; SAD FACES; CONNECTIVITY;

D O I：

10.1007/s11920-010-0160-4

中图分类号：

R749 [精神病学];

学科分类号：

100205 ;

摘要：

During the past several years, we have achieved a deeper understanding of the etiology/pathophysiology of major depressive disorder (MDD). However, this improved understanding has not translated to improved treatment outcome. Treatment often results in symptomatic improvement, but not full recovery. Clinical approaches are largely trial-and-error, and when the first treatment does not result in recovery for the patient, there is little proven scientific basis for choosing the next. One approach to enhancing treatment outcomes in MDD has been the use of standardized sequential treatment algorithms and measurement-based care. Such treatment algorithms stand in contrast to the personalized medicine approach, in which biomarkers would guide decision making. Incorporation of biomarker measurements into treatment algorithms could speed recovery from MDD by shortening or eliminating lengthy and ineffective trials. Recent research results suggest several classes of physiologic biomarkers may be useful for predicting response. These include brain structural or functional findings, as well as genomic, proteomic, and metabolomic measures. Recent data indicate that such measures, at baseline or early in the course of treatment, may constitute useful predictors of treatment outcome. Once such biomarkers are validated, they could form the basis of new paradigms for antidepressant treatment selection.

引用

页码：553 / 562

页数：10

共 89 条

[21] Prognostic and Diagnostic Potential of the Structural Neuroanatomy of Depression [J].