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Exploration of baseline and early changes in neurocognitive characteristics as predictors of treatment response to bupropion, sertraline, and placebo in the EMBARC clinical trial

Published online by Cambridge University Press:  20 November 2020

Yuen-Siang Ang ,
Gerard E. Bruder ,
John G. Keilp ,
Ashleigh Rutherford ,
Daniel M. Alschuler ,
Pia Pechtel ,
Christian A. Webb ,
Thomas Carmody ,
Maurizio Fava  and
Cristina Cusin
...Show all authors
Yuen-Siang Ang
Affiliation:
Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
Gerard E. Bruder
Affiliation:
Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
John G. Keilp
Affiliation:
Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
Ashleigh Rutherford
Affiliation:
Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
Daniel M. Alschuler
Affiliation:
Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
Pia Pechtel
Affiliation:
Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
Christian A. Webb
Affiliation:
Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA
Thomas Carmody
Affiliation:
Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas, USA
Maurizio Fava
Affiliation:
Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
Cristina Cusin
Affiliation:
Department of Psychiatry, Massachusetts General Hospital, Boston, Massachusetts, USA
Patrick J. McGrath
Affiliation:
Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
Myrna Weissman
Affiliation:
Department of Psychiatry, New York State Psychiatric Institute and Columbia University Vagelos College of Physicians and Surgeons, New York, USA
Ramin Parsey
Affiliation:
Department of Psychiatry, Stony Brook University, Stony Brook, New York, USA
Maria A. Oquendo
Affiliation:
Department of Psychiatry, University of Pennsylvania, Perelman School of Medicine, Philadelphia, Pennsylvania, USA
Melvin G. McInnis
Affiliation:
Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
Crystal M. Cooper
Affiliation:
Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas, USA
Patricia Deldin
Affiliation:
Department of Psychiatry, University of Michigan, Ann Arbor, Michigan, USA
Madhukar H. Trivedi
Affiliation:
Department of Psychiatry, University of Texas, Southwestern Medical Center, Dallas, Texas, USA
Diego A. Pizzagalli*
Affiliation:
Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA Center for Depression, Anxiety and Stress Research, McLean Hospital, Belmont, Massachusetts, USA McLean Imaging Center, McLean Hospital, Belmont, Massachusetts, USA
*
Author for correspondence: Diego A. Pizzagalli, E-mail: [email protected]
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Abstract

Background

Treatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner.

Methods

In the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16.

Results

Greater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline.

Conclusion

These exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.

Keywords

Biomarkersbupropioncognitive controldepressionplacebo responsereward learningsertralinetreatment response
Type
Original Article
Information
Psychological Medicine , Volume 52 , Issue 13 , October 2022 , pp. 2441 - 2449
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Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press.

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References

Alexopoulos, G. S., Manning, K., Kanellopoulos, D., McGovern, A., Seirup, J. K., Banerjee, S., & Gunning, F. (2015). Cognitive control, reward-related decision making and outcomes of late-life depression treated with an antidepressant. Psychological Medicine, 45(14), 3111–3120. doi:10.1017/S0033291715001075.CrossRefGoogle ScholarPubMed
Alexopoulos, G. S., Murphy, C. F., Gunning-Dixon, F. M., Kalayam, B., Katz, R., Kanellopoulos, D., … Foxe, J. J. (2007). Event-related potentials in an emotional go/no-go task and remission of geriatric depression. Neuroreport, 18(3), 217–221. doi:10.1097/WNR.0b013e328013ceda.CrossRefGoogle Scholar
Ang, Y.-S., Kaiser, R., Deckersbach, T., Almeida, J., Phillips, M. L., Chase, H. W., … Pizzagalli, D. A. (2020). Pretreatment reward sensitivity and frontostriatal resting-state functional connectivity are associated with response to bupropion after sertraline non-response. Biological Psychiatry, 88(8), 657–667.CrossRefGoogle Scholar
Baddeley, A. D. (1968). A 3 min reasoning test based on grammatical transformation. Psychonomic Science, 10(10), 341–342. doi:10.3758/BF03331551.CrossRefGoogle Scholar
Beblo, T., Baumann, B., Bogerts, B., Wallesch, C.-W., & Herrmann, M. (1999). Neuropsychological correlates of major depression: A short-term follow-up. Cognitive Neuropsychiatry, 4(4), 333–341. doi:10.1080/135468099395864.CrossRefGoogle Scholar
Benton, A. L., Hamsher, K., & Sivan, A. B. (1983). Multilingual aphasia Examination (3rd ed.). Iowa City, IA: AJA Associates.Google Scholar
Berridge, K. C., Robinson, T. E., & Aldridge, J. W. (2009). Dissecting components of reward: ‘liking’, ‘wanting’, and learning. Current Opinion in Pharmacology, 9(1), 65–73. doi: 10.1016/j.coph.2008.12.014.CrossRefGoogle Scholar
Bruder, G. E., Alvarenga, J. E., Alschuler, D., Abraham, K., Keilp, J. G., Hellerstein, D. J., … McGrath, P. J. (2014). Neurocognitive predictors of antidepressant clinical response. Journal of Affective Disorders, 166, 108–114. doi:10.1016/j.jad.2014.04.057.CrossRefGoogle ScholarPubMed
Cléry-Melin, M.-L., Gorwood, P. (2017). A simple attention test in the acute phase of a major depressive episode is predictive of later functional remission: Cléry-M Elin et al.. Depression and Anxiety, 34(2), 159–170. doi:10.1002/da.22575.CrossRefGoogle Scholar
Dunkin, J. J., Leuchter, A. F., Cook, I. A., Kasl-Godley, J. E., Abrams, M., & Rosenberg-Thompson, S. (2000). Executive dysfunction predicts nonresponse to fluoxetine in major depression. Journal of Affective Disorders, 60(1), 13–23.CrossRefGoogle ScholarPubMed
Durazzo, T. C., Meyerhoff, D. J., & Nixon, S. J. (2012). A comprehensive assessment of neurocognition in middle-aged chronic cigarette smokers. Drug and Alcohol Dependence, 122(1–2), 105–111. doi:10.1016/j.drugalcdep.2011.09.019.CrossRefGoogle ScholarPubMed
Enck, P., Bingel, U., Schedlowski, M., & Rief, W. (2013). The placebo response in medicine: Minimize, maximize or personalize? Nature Reviews Drug Discovery, 12(3), 191–204. doi:10.1038/nrd3923.CrossRefGoogle ScholarPubMed
Entsuah, R., & Vinall, P. (2007). Potential predictors of placebo response: Lessons from a large database. Drug Information Journal, 41(3), 315–330. doi:10.1177/009286150704100304.CrossRefGoogle Scholar
Eriksen, C. W. (1995). The flankers task and response competition: A useful tool for investigating a variety of cognitive problems. Visual Cognition, 2(2–3), 101–118. doi:10.1080/13506289508401726.CrossRefGoogle Scholar
Etkin, A., Patenaude, B., Song, Y. J. C., Usherwood, T., Rekshan, W., Schatzberg, A. F., … Williams, L. M. (2015). A cognitive-emotional biomarker for predicting remission with antidepressant medications: A report from the iSPOT-D trial. Neuropsychopharmacology, 40(6), 1332–1342. doi:10.1038/npp.2014.333.CrossRefGoogle ScholarPubMed
Fournier, J. C., DeRubeis, R. J., Hollon, S. D., Dimidjian, S., Amsterdam, J. D., Shelton, R. C., & Fawcett, J. (2010). Antidepressant drug effects and depression severity: A patient-level meta-analysis. JAMA, 303(1), 47. doi:10.1001/jama.2009.1943.CrossRefGoogle ScholarPubMed
Fredman, S. J., Fava, M., Kienke, A. S., White, C. N., Nierenberg, A. A., & Rosenbaum, J. F. (2000). Partial response, nonresponse, and relapse with selective serotonin reuptake inhibitors in major depression: A survey of current ‘next-step’ practices. The Journal of Clinical Psychiatry, 61(6), 403–408.CrossRefGoogle ScholarPubMed
Godlewska, B. R., Browning, M., Norbury, R., Cowen, P. J., & Harmer, C. J. (2016). Early changes in emotional processing as a marker of clinical response to SSRI treatment in depression. Translational Psychiatry, 6(11), e957. doi:10.1038/tp.2016.130.CrossRefGoogle ScholarPubMed
Gorlyn, M., Keilp, J. G., Grunebaum, M. F., Taylor, B. P., Oquendo, M. A., Bruder, G. E., … Mann, J. J. (2008). Neuropsychological characteristics as predictors of SSRI treatment response in depressed subjects. Journal of Neural Transmission, 115(8), 1213–1219. doi: 10.1007/s00702-008-0084-x.CrossRefGoogle ScholarPubMed
Gorwood, P., Vaiva, G., Corruble, E., Llorca, P.-M., Baylé, F. J., & Courtet, P. (2015). The ability of early changes in motivation to predict later antidepressant treatment response. Neuropsychiatric Disease and Treatment, 11, 2875–2882. doi:10.2147/NDT.S92795.Google ScholarPubMed
Greenberg, P. E., Fournier, A.-A., Sisitsky, T., Pike, C. T., & Kessler, R. C. (2015). The economic burden of adults with major depressive disorder in the United States (2005 and 2010). The Journal of Clinical Psychiatry, 76(02), 155–162. doi:10.4088/JCP.14m09298.CrossRefGoogle Scholar
Groves, S. J., Douglas, K. M., & Porter, R. J. (2018). A systematic review of cognitive predictors of treatment outcome in major depression. Frontiers in Psychiatry, 9, 382. doi: 10.3389/fpsyt.2018.00382.CrossRefGoogle ScholarPubMed
Gudayol-Ferré, E., Herrera-Guzmán, I., Camarena, B., Cortés-Penagos, C., Herrera-Abarca, J. E., Martínez-Medina, P., … Guàrdia-Olmos, J. (2010). The role of clinical variables, neuropsychological performance and SLC6A4 and COMT gene polymorphisms on the prediction of early response to fluoxetine in major depressive disorder. Journal of Affective Disorders, 127(1–3), 343–351. doi:10.1016/j.jad.2010.06.002.CrossRefGoogle ScholarPubMed
Gudayol-Ferré, E., Herrera-Guzmán, I., Camarena, B., Cortés-Penagos, C., Herrera-Abarca, J. E., Martínez-Medina, P., … Guàrdia-Olmos, J. (2012). Prediction of remission of depression with clinical variables, neuropsychological performance, and serotonergic/dopaminergic gene polymorphisms: Prediction of remission of depression. Human Psychopharmacology: Clinical and Experimental, 27(6), 577–586. doi:10.1002/hup.2267.CrossRefGoogle ScholarPubMed
Hamilton, M. (1960). A rating scale for depression. Journal of Neurology, Neurosurgery, and Psychiatry, 23, 56–62.CrossRefGoogle ScholarPubMed
Hammar, Ã, Sørensen, L., Ardal, G., Oedegaard, K. J., Kroken, R., Roness, A., … Lund, A. (2009). Enduring cognitive dysfunction in unipolar major depression: A test–retest study using the Stroop paradigm. Scandinavian Journal of Psychology, 51(4), 304–308. doi: 10.1111/j.1467-9450.2009.00765.x.Google ScholarPubMed
Herrera-Guzmán, I., Gudayol-Ferré, E., Lira-Mandujano, J., Herrera-Abarca, J., Herrera-Guzmán, D., Montoya-Pérez, K., & Guardia-Olmos, J. (2008). Cognitive predictors of treatment response to bupropion and cognitive effects of bupropion in patients with major depressive disorder. Psychiatry Research, 160(1), 72–82. doi:10.1016/j.psychres.2007.04.012,CrossRefGoogle ScholarPubMed
Herrera-Guzmán, I., Herrera-Abarca, J. E., Gudayol-Ferré, E., Herrera-Guzmán, D., Gómez-Carbajal, L., Peña-Olvira, M., … Joan, G.-O. (2010). Effects of selective serotonin reuptake and dual serotonergic–noradrenergic reuptake treatments on attention and executive functions in patients with major depressive disorder. Psychiatry Research, 177(3), 323–329. doi:10.1016/j.psychres.2010.03.006.CrossRefGoogle ScholarPubMed
Hinkelmann, K., Moritz, S., Botzenhardt, J., Muhtz, C., Wiedemann, K., Kellner, M., & Otte, C. (2012). Changes in cortisol secretion during antidepressive treatment and cognitive improvement in patients with major depression: A longitudinal study. Psychoneuroendocrinology, 37(5), 685–692. doi: 10.1016/j.psyneuen.2011.08.012.CrossRefGoogle ScholarPubMed
Holmes, R. D., Tiwari, A. K., & Kennedy, J. L. (2016). Mechanisms of the placebo effect in pain and psychiatric disorders. The Pharmacogenomics Journal, 16(6), 491–500. doi: 10.1038/tpj.2016.15.CrossRefGoogle ScholarPubMed
Huberty, C. J., & Morris, J. D. (1989). Multivariate analysis versus multiple univariate analyses. Psychological Bulletin, 105(2), 302–308. doi:10.1037/0033-2909.105.2.302.CrossRefGoogle Scholar
James, S. L., Abate, D., Abate, K. H., Abay, S. M., Abbafati, C., Abbasi, N., … Murray, C. J. L. (2018). Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017. The Lancet, 392(10159), 1789–1858. doi:10.1016/S0140-6736(18)32279-7.CrossRefGoogle Scholar
Kalayam, B., & Alexopoulos, G. S. (2003). A preliminary study of left frontal region error negativity and symptom improvement in geriatric depression. The American Journal of Psychiatry, 160(11), 2054–2056. doi:10.1176/appi.ajp.160.11.2054.CrossRefGoogle ScholarPubMed
Katon, W., Robinson, P., Von Korff, M., Lin, E., Bush, T., Ludman, E., … Walker, E. (1996). A multifaceted intervention to improve treatment of depression in primary care. Archives of General Psychiatry, 53(10), 924–932.CrossRefGoogle ScholarPubMed
Keilp, J. G., Sackeim, H. A., & Mann, J. J. (2005). Correlates of trait impulsiveness in performance measures and neuropsychological tests. Psychiatry Research, 135(3), 191–201. doi: 10.1016/j.psychres.2005.03.006.CrossRefGoogle ScholarPubMed
Kessler, R. C., Berglund, P., Demler, O., Jin, R., Koretz, D., Merikangas, K. R., … Wang, P. S. (2003). The epidemiology of major depressive disorder: Results from the national comorbidity survey replication (NCS-R). JAMA, 289(23), 3095. doi: 10.1001/jama.289.23.3095.CrossRefGoogle Scholar
Kirsch, I., Deacon, B. J., Huedo-Medina, T. B., Scoboria, A., Moore, T. J., & Johnson, B. T. (2008). Initial severity and antidepressant benefits: A meta-analysis of data submitted to the Food and Drug Administration. PLoS Medicine, 5(2), e45. doi:10.1371/journal.pmed.0050045.CrossRefGoogle ScholarPubMed
Leuchter, A. F., Cook, I. A., Witte, E. A., Morgan, M., & Abrams, M. (2002). Changes in brain function of depressed subjects during treatment with placebo. American Journal of Psychiatry, 159(1), 122–129. doi:10.1176/appi.ajp.159.1.122.CrossRefGoogle ScholarPubMed
Mayberg, H. S., Silva, J. A., Brannan, S. K., Tekell, J. L., Mahurin, R. K., McGinnis, S., & Jerabek, P. A. (2002). The functional neuroanatomy of the placebo effect. American Journal of Psychiatry, 159(5), 728–737. doi:10.1176/appi.ajp.159.5.728.CrossRefGoogle ScholarPubMed
Mikoteit, T., Hemmeter, U., Eckert, A., Brand, S., Bischof, R., Delini-Stula, A., … Beck, J. (2015). Improved alertness is associated with early increase in Serum brain-derived neurotrophic factor and antidepressant treatment outcome in major depression. Neuropsychobiology, 72(1), 16–28. doi:10.1159/000437439.CrossRefGoogle ScholarPubMed
Murrough, J. W., Burdick, K. E., Levitch, C. F., Perez, A. M., Brallier, J. W., Chang, L. C., … Iosifescu, D. V. (2015). Neurocognitive effects of ketamine and association with antidepressant response in individuals with treatment-resistant depression: A randomized controlled trial. Neuropsychopharmacology, 40(5), 1084–1090. doi: 10.1038/npp.2014.298.CrossRefGoogle ScholarPubMed
Murrough, J. W., Wan, L.-B., Iacoviello, B., Collins, K. A., Solon, C., Glicksberg, B., … Burdick, K. E. (2014). Neurocognitive effects of ketamine in treatment-resistant major depression: Association with antidepressant response. Psychopharmacology, 231, 481–488. doi: 10.1007/s00213-013-3255-x.CrossRefGoogle Scholar
Nooyens, A. C. J., van Gelder, B. M., & Verschuren, W. M. M. (2008). Smoking and cognitive decline among middle-aged men and women: The Doetinchem Cohort Study. American Journal of Public Health, 98(12), 2244–2250. doi:10.2105/AJPH.2007.130294.CrossRefGoogle ScholarPubMed
Pizzagalli, D. A., Jahn, A. L., & O'Shea, J. P. (2005). Toward an objective characterization of an anhedonic phenotype: A signal-detection approach. Biological Psychiatry, 57(4), 319–327. doi: 10.1016/j.biopsych.2004.11.026.CrossRefGoogle ScholarPubMed
Pizzagalli, D. A., Webb, C. A., Dillon, D. G., Tenke, C. E., Kayser, J., Goer, F., … Trivedi, M. H. (2018). Pretreatment rostral anterior cingulate cortex theta activity in relation to symptom improvement in depression: A randomized clinical trial. JAMA Psychiatry, 75(6), 547. doi:10.1001/jamapsychiatry.2018.0252.CrossRefGoogle ScholarPubMed
Reppermund, S., Ising, M., Lucae, S., & Zihl, J. (2009). Cognitive impairment in unipolar depression is persistent and non-specific: Further evidence for the final common pathway disorder hypothesis. Psychological Medicine, 39(4), 603–614. doi:10.1017/S003329170800411X.CrossRefGoogle ScholarPubMed
Reppermund, S., Zihl, J., Lucae, S., Horstmann, S., Kloiber, S., Holsboer, F., & Ising, M. (2007). Persistent cognitive impairment in depression: The role of psychopathology and altered hypothalamic-pituitary-adrenocortical (HPA) system regulation. Biological Psychiatry, 62(5), 400–406. doi: 10.1016/j.biopsych.2006.09.027.CrossRefGoogle ScholarPubMed
Rush, A. J., Trivedi, M. H., Ibrahim, H. M., Carmody, T. J., Arnow, B., Klein, D. N., … Keller, M. B. (2003). The 16-item Quick Inventory of Depressive Symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): A psychometric evaluation in patients with chronic major depression. Biological Psychiatry, 54(5), 573–583.CrossRefGoogle ScholarPubMed
Rush, A. J., Trivedi, M. H., Wisniewski, S. R., Nierenberg, A. A., Stewart, J. W., Warden, D., … Fava, M. (2006). Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: A STAR*D report. American Journal of Psychiatry, 163(11), 1905–1917. doi:10.1176/ajp.2006.163.11.1905.CrossRefGoogle ScholarPubMed
Schatzberg, A. F. (2015). Issues encountered in recent attempts to develop novel antidepressant agents: Developing new antidepressant agents. Annals of the New York Academy of Sciences, 1345(1), 67–73. doi: 10.1111/nyas.12716.CrossRefGoogle Scholar
Shiroma, P. R., Albott, C. S., Johns, B., Thuras, P., Wels, J., & Lim, K. O. (2014). Neurocognitive performance and serial intravenous subanesthetic ketamine in treatment-resistant depression. The International Journal of Neuropsychopharmacology, 17(11), 1805–1813. doi: 10.1017/S1461145714001011.CrossRefGoogle ScholarPubMed
Shiroma, P. R., Thuras, P., Johns, B., & Lim, K. O. (2014). Emotion recognition processing as early predictor of response to 8-week citalopram treatment in late-life depression: Emotion recognition in late-life depression. International Journal of Geriatric Psychiatry, 29(11), 1132–1139. doi: 10.1002/gps.4104.CrossRefGoogle ScholarPubMed
Sneed, J. R., Roose, S. P., Keilp, J. G., Krishnan, K. R. R., Alexopoulos, G. S., & Sackeim, H. A. (2007). Response inhibition predicts poor antidepressant treatment response in very old depressed patients. The American Journal of Geriatric Psychiatry, 15(7), 553–563. doi: 10.1097/JGP.0b013e3180302513.CrossRefGoogle ScholarPubMed
Souery, D., Papakostas, G. I., & Trivedi, M. H. (2006). Treatment-resistant depression. The Journal of Clinical Psychiatry, 67(Suppl 6), 16–22.Google ScholarPubMed
Taylor, B. P., Bruder, G. E., Stewart, J. W., McGrath, P. J., Halperin, J., Ehrlichman, H., & Quitkin, F. M. (2006). Psychomotor slowing as a predictor of fluoxetine nonresponse in depressed outpatients. The American Journal of Psychiatry, 163(1), 73–78. doi:10.1176/appi.ajp.163.1.73.CrossRefGoogle ScholarPubMed
Thorne, D. R., Genser, S. G., Sing, H. C., & Hegge, F. W. (1985). The Walter Reed performance assessment battery. Neurobehavioral Toxicology and Teratology, 7(4), 415–418.Google ScholarPubMed
Tranter, R., Bell, D., Gutting, P., Harmer, C., Healy, D., & Anderson, I. M. (2009). The effect of serotonergic and noradrenergic antidepressants on face emotion processing in depressed patients. Journal of Affective Disorders, 118(1–3), 87–93. doi:10.1016/j.jad.2009.01.028.CrossRefGoogle ScholarPubMed
Trivedi, M. H., McGrath, P. J., Fava, M., Parsey, R. V., Kurian, B. T., Phillips, M. L., … Weissman, M. M. (2016). Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): Rationale and design. Journal of Psychiatric Research, 78, 11–23. doi:10.1016/j.jpsychires.2016.03.001.CrossRefGoogle ScholarPubMed
Trivedi, M. H., Rush, A. J., Wisniewski, S. R., Nierenberg, A. A., Warden, D., Ritz, L., … STAR*D Study Team. (2006). Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: Implications for clinical practice. American Journal of Psychiatry, 163(1), 28–40. doi:10.1176/appi.ajp.163.1.28.CrossRefGoogle ScholarPubMed
Trivedi, M. H., South, C., Jha, M. K., Rush, A. J., Cao, J., Kurian, B., … Fava, M. (2018). A novel strategy to identify placebo responders: Prediction index of clinical and biological markers in the EMBARC trial. Psychotherapy and Psychosomatics, 87(5), 285–295. doi:10.1159/000491093.CrossRefGoogle ScholarPubMed
Vrieze, E., Pizzagalli, D. A., Demyttenaere, K., Hompes, T., Sienaert, P., de Boer, P., … Claes, S. (2013). Reduced reward learning predicts outcome in major depressive disorder. Biological Psychiatry, 73(7), 639–645. doi:10.1016/j.biopsych.2012.10.014.CrossRefGoogle ScholarPubMed
Whitton, A. E., Reinen, J. M., Slifstein, M., Ang, Y.-S., McGrath, P. J., Iosifescu, D. V., … Schneier, F. R. (2020). Baseline reward processing and ventrostriatal dopamine function are associated with pramipexole response in depression. Brain, 143(2), 701–710. doi: 10.1093/brain/awaa002.CrossRefGoogle ScholarPubMed
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