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Improving the Prediction of Treatment Response in Depression: Integration of Clinical, Cognitive, Psychophysiological, Neuroimaging, and Genetic Measures

Published online by Cambridge University Press:  07 November 2014

Abstract

Antidepressants are important in the treatment of depression, and selective serotonin reuptake inhibitors are first-line pharmacologic options. However, only 50% to 70% of patients respond to first treatment and <40% remit. Since depression is associated with substantial morbidity, mortality, and family burden, it is unfortunate and demanding on health resources that patients must remain on their prescribed medications for at least 4 weeks without knowing whether the particular antidepressant will be effective. Studies have suggested a number of predictors of treatment response, including clinical, psychophysiological, neuroimaging, and genetics, each with varying degrees of success and nearly all with poor prognostic sensitivity and specificity. Studies are yet to be conducted that use multiple measures from these different domains to determine whether sensitivity and specificity can be improved to predict individual treatment response. It is proposed that a focus on standardized testing methodologies across multiple testing modalities and their integration will be crucial for translation of research findings into clinical practice.

Type
Review Articles
Copyright
Copyright © Cambridge University Press 2008

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References

REFERENCES

1.Diagnostic and Statistical Manual of Mental Disorders. 4th ed, text rev. Washington, DC: American Psychiatric Association; 2000.Google Scholar
2.Judd, LL, Akiskal, HS, Zeller, PJ, et al.Psychosocial disability during the long-term course of unipolar major depressive disorder. Arch Gen Psychiatry. 2000;57:375380.Google Scholar
3.Murray, C, Lopez, A. Global Health Statistics: A Compendium of Incidence, Prevalence and Mortality Estimates for Over 2000 Conditions. Available at: www.popline.org/docs/1203/253379.html. Accessed November 6, 2008.Google Scholar
4.Gartlehner, G, Hansen, RA, Thieda, P, et al. Comparative effectiveness of second-generation antidepressants in the pharmacologic treatment of adult depression. Comparative effectiveness review no. 7. Available at: http://effectivehealthcare.ahrq.gov/healthInfo.cfm?infotype=rr&ProcessID=7&DocID=61. Accessed November 6, 2008.Google Scholar
5.Kornstein, SG, Schneider, RK. Clinical features of treatment-resistant depression. J Clin Psychiatry. 2001;62:1825.Google Scholar
6.Berrettini, W. Psychiatric pharmacogenetics: a developing science. Neuropsychopharmacology. 2002;26:128129.Google Scholar
7.Trivedi, MH, Rush, AJ, Wisniewski, SR, et al.Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry. 2006;163:2840.CrossRefGoogle ScholarPubMed
8.Kirsch, I, Deacon, BJ, Huedo-Medina, TB, Scoboria, A, Moore, TJ, Johnson, BT. Initial severity and antidepressant benefits: a meta-analysis of data submitted to the Food and Drug Administration. PLoS Med. 2008;5:e45.CrossRefGoogle ScholarPubMed
9.Parker, G. Classifying depression: should paradigms lost be regained? Am J Psychiatry. 2000;157:11951203.CrossRefGoogle ScholarPubMed
10.Clark, LA, Watson, D. Tripartite model of anxiety and depression: psychometric evidence and taxonomic implications. J Abnorm Psychol. 1991;100:316336.Google Scholar
11.Parker, G, Roy, K, Mitchell, P, Wilhelm, K, Malhi, G, Hadzi-Pavlovic, D. Atypical depression: a reappraisal. Am J Psychiatry. 2002;159:14701479.Google Scholar
12.Goodwin, FK. Predictors of antidepressant response. Bull Menninger Clin. 1993;57:146160.Google Scholar
13.Taylor, BP, Bruder, GE, Stewart, JW, et al.Psychomotor slowing as a predictor of fluoxetine nonresponse in depressed outpatients. Am J Psychiatry. 2006;163:7378.CrossRefGoogle ScholarPubMed
14.Mitchell, PB. Managing depression in a community setting. Med J Aust. 1997;167:383388.Google Scholar
15.Mitchell, PB. The new antidepressants—are they worth the cost? Aust Prescriber. 1995;18:8284.Google Scholar
16.Janke, W. Clinical efficacy of drugs predicted from drug effects after short-term administration in animals, normal subjects, and patients. Neuropsychobiology. 1985;13:5354.Google Scholar
17.Cowdry, R, Goodwin, F. Biological and physiological predictors of drug response. In: van Praag, HM, Lader, Mh, Rafelsen, OJ, eds. Handbook of Biological Psychiatry. 1st ed. New York, NY: Marcel Dekker; 1981:263308.Google Scholar
18.Bielski, RJ, Friedel, RO. Prediction of tricyclic antidepressant response: a critical review. Arch Gen Psychiatry. 1976;33:14791489.CrossRefGoogle ScholarPubMed
19.Joyce, PR, Paykel, ES. Predictors of drug response in depression. Arch Gen Psychiatry. 1989;46:8999.Google Scholar
20.Mayberg, HS, Brannan, SK, Mahurin, RK, et al.Cingulate function in depression: a potential predictor of treatment response. Neuroreport. 1997;8:10571061.CrossRefGoogle ScholarPubMed
21.Davidson, RJ, Irwin, W, Anderle, MJ, Kalin, NH. The neural substrates of affective processing in depressed patients treated with venlafaxine. Am J Psychiatry. 2003;160:6475.Google Scholar
22.Kemp, AH, Gray, MA, Silberstein, RB, Armstrong, SM, Nathan, PJ. Augmentation of serotonin enhances pleasant and suppresses unpleasant cortical electrophysiological responses to visual emotional stimuli in humans. Neuroimage. 2004;22:10841096.Google Scholar
23.Kemp, AH, Gray, MA, Line, P, Silberstein, BB, Nathan, PJ. Preliminary electrophysiological evidence for modulation of the processing of negative affect by serotonin. Brain Cogn. 2003;51:198200.Google Scholar
24.Harmer, CJ, Bhagwagar, Z, Perrett, DI, Vollm, BA, Cowen, PJ, Goodwin, GM. Acute SSRI administration affects the processing of social cues in healthy volunteers. Neuropsychopharmacology. 2003;28:148152.CrossRefGoogle ScholarPubMed
25.Harmer, CJ, Hill, SA, Taylor, MJ, Cowen, PJ, Goodwin, GM. Toward a neuropsychological theory of antidepressant drug action: increase in positive emotional bias after potentiation of norepinephrine activity. Am J Psychiatry. 2003;160:990992.CrossRefGoogle Scholar
26.Harmer, CJ, Mackay, CE, Reid, CB, Cowen, PJ, Goodwin, GM. Antidepressant drug treatment modifies the neural processing of nonconscious threat cues. Biol Psychiatry. 2006;59:816820.Google Scholar
27.Segal, ZV, Kennedy, S, Gemar, M, Hood, K, Pedersen, R, Buis, T. Cognitive reactivity to sad mood provocation and the prediction of depressive relapse. Arch Gen Psychiatry. 2006;63:749755.CrossRefGoogle ScholarPubMed
28.Keller, MB. Past, present, and future directions for defining optimal treatment outcome in depression: remission and beyond. JAMA. 2003;289:31523160.Google Scholar
29.Souery, D, Papakostas, GI, Trivedi, MH. Treatment-resistant depression. J Clin Psychiatry. 2006;67(suppl 6):1622.Google Scholar
30.Keller, MB. Remission versus response: the new gold standard of antidepressant care. J Clin Psychiatry. 2004;65(suppl 4):5359.Google Scholar
31.Kleindienst, N, Engel, R, Greil, W. Which clinical factors predict response to prophylactic lithium? A systematic review for bipolar disorders. Bipolar Disord. 2005;7:404417.Google Scholar
32.Benazzi, F. The continuum/spectrum concept of mood disorders: is mixed depression the basic link? Eur Arch Psychiatry Clin Neurosci. 2006;256:512515.Google Scholar
33.Alexopoulos, GS, Meyers, BS, Young, RC, Kakuma, T, Silbersweig, D, Charlson, M. Clinically defined vascular depression. Am J Psychiatry. 1997;154:562565.Google ScholarPubMed
34.Herrmann, LL, Le Masurier, M, Ebmeier, KP. White matter hyperintensities in late life depression: a systematic review. J Neural Neurosurg Psychiatry. 2007;79:619624.CrossRefGoogle ScholarPubMed
35.Hirschfeld, RMA. Psychosocial predictors of outcome in depression. In: Bloom, FE, Kupfer, DJ, eds. Psychopharmacology: The Fourth Generation of Progress. New York, NY: Raven Press; 2002:11131121.Google Scholar
36.Bagby, RM, Ryder, AG, Cristi, C. Psychosocial and clinical predictors of response to pharmacotherapy for depression. J Psychiatry Neurosci. 2002;27:250257.Google Scholar
37.Sotsky, SM, Glass, DR, Shea, MT, et al.Patient predictors of response to psychotherapy and pharmacotherapy: findings in the NIMH Treatment of Depression Collaborative Research Program. Am J Psychiatry. 1991;148:9971008.Google Scholar
38.National Institute for Clinical Excellence. Depression: Management of Depression in Primary and Secondary Care. London, UK: National Institute for Clinical Excellence (NICE); 2004.Google Scholar
39.Montgomery, SA, Baldwin, DS, Blier, P, et al.Which antidepressants have demonstrated superior efficacy? A review of the evidence. Int Clin Psychopharmacol. 2007;22:323329.Google Scholar
40.Einarson, TR. Evidence based review of escitalopram in treating major depressive disorder in primary care. Int Clin Psychopharmacol. 2004;19:305310.CrossRefGoogle ScholarPubMed
41.Fernandez, JL, Montgomery, S, Francois, C. Evaluation of the cost effectiveness of escitalopram versus venlafaxine XR in major depressive disorder. Pharmacoeconomics. 2005;23:155167.Google Scholar
42.Eckert, L, Falissard, B. Using meta-regression in performing indirect-comparisons: comparing escitalopram with venlafaxine XR. Curr Med Res Opin. 2006;22:23132321.Google Scholar
43.Liebowitz, MR, Quitkin, FM, Stewart, JW, et al.Antidepressant specificity in atypical depression. Arch Gen Psychiatry. 1988;45:129137.Google Scholar
44.Thase, ME, Trivedi, MH, Rush, AJ. MAOIs in the contemporary treatment of depression. Neuropsychopharmacology. 1995;12:185219.CrossRefGoogle ScholarPubMed
45.Anderson, IM. SSRIS versus tricyclic antidepressants in depressed inpatients: a meta-analysis of efficacy and tolerability. Depress Anxiety. 1998;7:1117.Google Scholar
46.Souery, D, Oswald, P, Massat, I, et al.Clinical factors associated with treatment resistance in major depressive disorder: results from a European multicenter study. J Clin Psychiatry. 2007;68:10621070.Google Scholar
47.Fava, M, Rush, AJ, Alpert, JE, et al.Difference in treatment outcome in outpatients with anxious versus nonanxious depression: a STAR*D report. Am J Psychiatry. 2008;165:342351.Google Scholar
48.Davidson, JR, Meoni, P, Haudiquet, V, Cantillon, M, Hackett, D. Achieving remission with venlafaxine and fluoxetine in major depression: its relationship to anxiety symptoms. Depress Anxiety. 2002;16:413.Google Scholar
49.Bakish, D. The patient with comorbid depression and anxiety: the unmet need. J Clin Psychiatry. 1999;60(suppl 6):2024.Google Scholar
50.Janssen, J, Pol, HE, Schnack, HG, et al.Cerebral volume measurements and subcortical white matter lesions and short-term treatment response in late life depression. Int J Geriatr Psychiatry. 2007;22:468474.CrossRefGoogle ScholarPubMed
51.Alexopoulos, GS, Meyers, BS, Young, RC, Campbell, S, Silbersweig, D, Charlson, M. ‘Vascular depression’ hypothesis. Arch Gen Psychiatry. 1997;54:915922.Google Scholar
52.Taylor, WD, Steffens, DC, MacFall, JR, et al.White matter hyperintensity progression and late-life depression outcomes. Arch Gen Psychiatry. 2003;60:10901096.Google Scholar
53.Baldwin, R, Jeffries, S, Jackson, A, et al.Treatment response in late-onset depression: relationship to neuropsychological, neuroradiological and vascular risk factors. Psychol Med. 2004;34:125136.Google Scholar
54.Salloway, S, Malloy, P, Kohn, R, et al.MRI and neuropsychological differences in early- and late-life-onset geriatric depression. Neurology. 1996;46:15671574.Google Scholar
55.Teodorczuk, A, O'Brien, JT, Firbank, MJ, et al.White matter changes and late-life depressive symptoms: longitudinal study. Br J Psychiatry. 2007;191:212217.CrossRefGoogle ScholarPubMed
56.Simpson, SW, Jackson, A, Baldwin, RC, Burns, A. 1997 IPA/Bayer Research Awards in Psychogeriatrics. Subcortical hyperintensities in late-life depression: acute response to treatment and neuropsychological impairment. Int Psychogeriatr. 1997;9(3):257275.CrossRefGoogle ScholarPubMed
57.Joffe, RT, Gatt, JM, Kemp, AH, et al.Brain derived neurotrophic factor Val66Met polymorphism, the five factor model of personality and hippocampal volume: Implications for depressive illness. Hum Brain Mapp. Jun 11 2008. [Epub ahead of print].Google Scholar
58.Shifman, S, Bhomra, A, Smiley, S, et al.A whole genome association study of neuroticism using DNA pooling. Mol Psychiatry. 2008;13:302312.Google Scholar
59.van den Oord, EJ, Kuo, PH, Hartmann, AM, et al.Genomewide association analysis followed by a replication study implicates a novel candidate gene for neuroticism. Arch Gen Psychiatry. 2008;65(9):10621071.Google Scholar
60.Hettema, JM, Neale, MC, Myers, JM, Prescott, CA, Kendler, KS. A population-based twin study of the relationship between neuroticism and internalizing disorders. Am J Psychiatry. 2006;163:857864.Google Scholar
61.Quitkin, FM. Placebos, drug effects, and study design: a clinician's guide. Am J Psychiatry. 1999;156:829836.Google Scholar
62.Peselow, ED, Fieve, RR, DiFiglia, C, Nelson, EC, Cloninger, CR. Personality traits and response to desipramine. The tridimensional personality questionnaire as a predictor of response to nefazodone treatment of depression. J Affect Disord. 1992;24:209216.Google Scholar
63.Nelson, EC, Cloninger, CR. The tridimensional personality questionnaire as a predictor of response to nefazodone treatment of depression. J Affect Disord. 1995;35:5157.Google Scholar
64.Clark, LA, Watson, D, Mineka, S. Temperament, personality, and the mood and anxiety disorders. J Abnorm Psychol. 1994;103:103116.Google Scholar
65.Mulder, RT, Joyce, PR, Luty, SE. The relationship of personality disorders to treatment outcome in depressed outpatients. J Clin Psychiatry. 2003;64:259264.Google Scholar
66.Kaufman, J, Charney, D. Effects of early stress on brain structure and function: implications for understanding the relationship between child maltreatment and depression. Dev Psychopathol. 2001;13:451471.Google Scholar
67.Nemeroff, CB, Heim, CM, Thase, ME, et al.Differential responses to psychotherapy versus pharmacotherapy in patients with chronic forms of major depression and childhood trauma. Proc Natl Acad Sci U S A. 2003;100:1429314296.Google Scholar
68.Papakostas, GI, Petersen, T, Denninger, JW, et al.Psychosocial functioning during the treatment of major depressive disorder with fluoxetine. J Clin Psychopharmacol. 2004;24:507511.Google Scholar
69.Tedlow, J, Fava, M. Uebelacker, L, Nierenberg, AA, Alpert, JE, Rosenbaum, J. Outcome definitions and predictors in depression. Psychother Psychosom. 1998;67:266270.Google Scholar
70.Trivedi, MH, Baker, SM. Clinical significance of monitoring early symptom change to predict outcome. J Clin Psychiatry. 2001;62:2733.Google Scholar
71.Mulder, RT, Joyce, PR, Sullivan, PF, Oakley-Browne, MA. Intimate bonds in depression. J Affect Disord. 1996;40:175178.Google Scholar
72.Lam, RW, Bartley, S, Yatham, LN, Tarn, EM, Zis, AP. Clinical predictors of short-term outcome in electroconvulsive therapy. Can J Psychiatry. 1999;44:158163.Google Scholar
73.Moller, HJ, Fischer, G, von Zerssen, D. Prediction of therapeutic response in acute treatment with antidepressants. Results of an empirical study involving 159 endogenous depressive inpatients. Eur Arch Psychiatry Neurol Sci. 1987;236:349357.Google Scholar
74.Moller, HJ, Krokenberger, M, von Zerssen, D. Prediction of short-term outcome of neurotic-depressive inpatients. Results of an empirical study of 134 inpatients. Bur Arch Psychiatry Clin Neurosci. 1993;242:301309.Google Scholar
75.Small, GW, Hamilton, SH, Bystritsky, A, Meyers, BS, Nemeroff, CB. Clinical response predictors in a double-blind, placebo-controlled trial of fluoxetine for geriatric major depression. Fluoxetine Collaborative Study Group. Int Psychogeriatr. 1995;7:4153.Google Scholar
76.Gartlehner, G, Hansen, RA, Thieda, P, et al.Comparative Effectiveness of Second-Generation Antidepressants in the Pharmacologic Treatment of Adult Depression. Comparative Effectiveness Review No. 7. (Prepared by RTI International-University of North Carolina Evidence-based Practice Center under Contract No. 290-02-0016.). Rockville, MD: Agency for Healthcare Research and Quality; 2007. Comparative Effectiveness Review No. 7.Google Scholar
77.Mayberg, HS, Silva, JA, Brannan, SK, et al.The functional neuroanatomy of the placebo effect. Am J Psychiatry. 2002;159:728737.Google Scholar
78.Goodwin, GM. Neuropsychological and neuroimaging evidence for the involvement of the frontal lobes in depression. J Psychopharmacol. 1997;11:115122.CrossRefGoogle ScholarPubMed
79.Rogers, MA, Kasai, K, Koji, M, et al.Executive and prefrontal dysfunction in unipolar depression: a review of neuropsychological and imaging evidence. Neurosci Res. 2004;50:111.CrossRefGoogle ScholarPubMed
80.Austin, MP, Mitchell, P, Goodwin, GM. Cognitive deficits in depression: possible implications for functional neuropathology. Br J Psychiatry. 2001;178:200206.Google Scholar
81.Rowe, DL, Cooper, NJ, Liddell, BJ, Clark, CR, Gordon, E, Williams, LM. Brain structure and function correlates of general and social cognition. J Integr Neurosci. 2007;6:3574.Google Scholar
82.Williams, LM, Whitford, TJ, Flynn, G, et al.General and social cognition in first episode schizophrenia: identification of separable factors and prediction of functional outcome using the IntegNeuro test battery. Schizophr Res. 2008;99:182191.Google Scholar
83.Dunkin, JJ, Leuchter, AF, Cook, IA, Kasl-Godley, JE, Abrams, M, Rosenberg-Thompson, S. Executive dysfunction predicts nonresponse to fluoxetine in major depression. J Affect Disord. 2000;60:1323.Google Scholar
84.Gorlyn, M, Keilp, JG, Grunebaum, MF, et al.Neuropsychological characteristics as predictors of SSRI treatment response in depressed subjects. J Neural Transm. 2008;115:12131219.Google Scholar
85.Herrmann, LL, Goodwin, GM, Ebmeier, KP. The cognitive neuropsychology of depression in the elderly. Psychol Med. 2007;37:16931702.CrossRefGoogle ScholarPubMed
86.Bruder, GE, Stewart, JW, Merrier, MA, et al.Outcome of cognitive-behavioral therapy for depression: relation to hemispheric dominance for verbal processing. J Abnorm Psychol. 1997;106:138144.Google Scholar
87.Bruder, GE, Otto, MW, McGrath, PJ, et al.Dichotic listening before and after fluoxetine treatment for major depression: relations of laterally to therapeutic response. Neuropsychopharmacology. 1996;15:171179.Google Scholar
88.Bruder, GE, Stewart, JW, Voglmaier, MM, et al.Cerebral laterality and depression: relations of perceptual asymmetry to outcome of treatment with tricyclic antidepressants. Neuropsychopharmacology. 1990;3:110.Google ScholarPubMed
89.Bruder, GE, Stewart, JW, Schaller, JD, McGrath, PJ. Predicting therapeutic response to secondary treatment with bupropion: dichotic listening tests of functional brain asymmetry. Psychiatry Res. 2007;153:137143.Google Scholar
90.Flament, MF, Lane, RM, Zhu, R, Ying, Z. Predictors of an acute antidepressant response to fluoxetine and sertraline. Int Clin Psychopharmacol. 1999;14:259275.Google Scholar
91.Caligiuri, MP, Gentili, V, Eberson, S, Kelsoe, J, Rapaport, M, Gillin, JC. A quantitative neuromotor predictor of antidepressant non-response in patients with major depression. J Affect Disord. 2003;77:135141.Google Scholar
92.Malhi, GS, Parker, GB, Greenwood, J. Structural and functional models of depression: from subtypes to substrates. Acta Psychiatr Scand. 2005;111:94105.Google Scholar
93.Rush, AJ, Wisniewski, SR, Warden, D, et al.Selecting among second-step antidepressant medication monotherapies: are clinical, demographic, or first-step treatment results informative? Arch Gen Psychiatry. 2008;65:870880.Google Scholar
94.Fava, M, Rush, AJ, Trivedi, MH, et al.Background and rationale for the sequenced treatment alternatives to relieve depression |STAR*D) study. Psychiatr Clin North Am. 2003;26:457494.Google Scholar
95.Rush, AJ, Fava, M, Wisniewski, SR, et al.Sequenced treatment alternatives to relieve depression (STAR*D): rationale and design. Control Clin Trials. 2004;25:119142.Google Scholar
96.Kampf-Sherf, O, Zlotogorski, Z, Gilboa, A, et al.Neuropsychological functioning in major depression and responsiveness to selective serotonin reuptake inhibitors antidepressants. J Affect Disord. 2004;82:453459.Google Scholar
97.Kramer-Ginsberg, E, Greenwald, BS, Krishnan, KR, et al.Neuropsychological functioning and MRI signal hyperintensities in geriatric depression. Am J Psychiatry. 1999;156:438444.Google Scholar
98.Stahl, SM, Zhang, L, Damatarca, C, Grady, M. Brain circuits determine destiny in depression: a novel approach to the psychopharmacology of wakefulness, fatigue, and executive dysfunction in major depressive disorder. J Clin Psychiatry. 2003;64:617.Google Scholar
99.de Groot, MH, Nolen, WA, Huijsman, AM, Bouvy, PF. Lateralized neuropsychological functioning in depressive patients before and after drug therapy. Biol Psychiatry. 1996;40:12821287.Google Scholar
100.Heller, W. Neuropsychological mechanisms of individual differences in emotion, personality, and arousal. Neuropsychology. 1993;7:476489.Google Scholar
101.Otto, MW, Fava, M, Rosenbaum, JF, Murphy, CF. Perceptual asymmetry, plasma cortisol, and response to treatment in depressed outpatients. Biol Psychiatry. 1991;30:703710.Google Scholar
102.Venn, HR, Watson, S, Gallagher, P, Young, AH. Facial expression perception: an objective outcome measure for treatment studies in mood disorders? Int J Neuropsychopharmacol. 2006;9:229245.Google Scholar
103.Keefe, RS. The contribution of neuropsychology to psychiatry. Am J Psychiatry. 1995;152:615.Google Scholar
104.Saletu, B, Grunberger, J, Linzmayer, L. On central effects of serotonin re-uptake inhibitors: quantitative EEG and psychometric studies with sertraline and zimelidine. J Neural Transm. 1986;67:241266.Google Scholar
105.Luthringer, R, Dago, KT, Patat, A, et al.Pharmacoelectroencephalographic profile of befloxatone, a new reversible MAO-A inhibitor, in healthy subjects. Neuropsychobiology. 1996;34:98105.Google Scholar
106.Argyropoulos, SV, Wilson, SJ. Sleep disturbances in depression and the effects of antidepressants. Int Rev Psychiatry. 2005;17:237245.Google Scholar
107.Benca, RM, Obermeyer, WH, Thisted, RA, Gillin, JC. Sleep and psychiatric disorders. A meta-analysis. Arch Gen Psychiatry. 1992;49:651668; discussion 669-670.Google Scholar
108.Taylor, MA, Fink, M. Restoring melancholia in the classification of mood disorders. J Affect Disord. 2008;105:114.Google Scholar
109.Thase, ME. Depression, sleep, and antidepressants. J Clin Psychiatry. 1998;59(suppl 4):5565.Google Scholar
110.Vogel, GW, Buffenstein, A, Minter, K, Hennessey, A. Drug effects on REM sleep and on endogenous depression. Neurosci Biobehav Rev. 1990;14:4963.Google Scholar
111.Gillin, JC, Wyatt, RJ, Fram, D, Snyder, F. The relationship between changes in REM sleep and clinical improvement in depressed patients treated with amitriptyline. Psychopharmacology (Berl). 1978;59:267272.Google Scholar
112.Kupfer, DJ, Spiker, DG, Coble, PA, Neil, JF, Ulrich, R, Shaw, DH. Sleep and treatment prediction in endogenous depression. Am J Psychiatry. 1981;138:429434.Google Scholar
113.Ehlers, CL, Havstad, JW, Kupfer, DJ. Estimation of the time course of slow-wave sleep over the night in depressed patients: effects of clomipramine and clinical response. Biol Psychiatry. 1996;39:171181.Google Scholar
114.Luthringer, R, Minot, R, Toussaint, M, Calvi-Gries, F, Schaltenbrand, N, Macher, JP. All-night EEG spectral analysis as a tool for the prediction of clinical response to antidepressant treatment. Biol Psychiatry. 1995;38:98104.Google Scholar
115.Staedt, J, Hunerjager, H, Ruther, E, Stoppe, G. Sleep cluster arousal analysis and treatment response to heterocyclic antidepressants in patients with major depression. J Affect Disord. 1998;49:221227.Google Scholar
116.Buysse, DJ, Hall, M, Begley, A, et al.Sleep and treatment response in depression: new findings using power spectral analysis. Psychiatry Res. 2001;103:5167.Google Scholar
117.Knott, VJ, Telner, JI, Lapierre, YD, Browne, M, Horn, ER. Qantitative EEG in the prediction of antidepressant response to imipramine. J Affect Disord. 1996;39:175184.Google Scholar
118.Knott, V, Mahoney, C, Kennedy, S, Evans, K. Pre-treatment EEG and it's relationship to depression severity and paroxetine treatment outcome. Pharmacopsychiatry. 2000;33:201205.Google Scholar
119.Knott, V, Mahoney, C, Kennedy, S, Evans, K. EEG correlates ot acute and chronic paroxetine treatment in depression. J Affect Disord. 2002;69:241249.Google Scholar
120.Mulert, C, Juckel, G, Brunnmeier, M, et al.Prediction of treatment response in major depression: integration of concepts. J Affect Disord. 2007;98:215225.Google Scholar
121.Pizzagalli, D, Pascual-Marqui, RD, Nitschke, JB, et al.Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis. Am J Psychiatry. 2001;158:405415.Google Scholar
122.Nystrom, C, Matousek, M, Hallstrom, T. Relationships between EEG and biochemical parameters in major depressive disorder. Acta Psychiatr Scand. 1988;77:457462.Google Scholar
123.Nieber, D, Schlegel, S. Relationships between psychomotor retardation and EEG power spectrum in major depression. Neuropsychobiology. 1992;25:2023.Google Scholar
124.Cook, IA, Leuchter, AF, Morgan, M, et al.Early changes in prefrontal activity characterize clinical respondersto antidepressants. Neuropsychopharmacology. 2002;27:120131.Google Scholar
125.Prichep, LS, Mas, F, Hollander, E, et al.Quantitative electroencephalographic subtyping of obsessive-compulsive disorder. Psychiatry Res. 1993;50:2532.Google Scholar
126.Suffin, SC, Emory, WH. Neurometric subgroups in attentional and affective disorders and their association with pharmacotherapeutic outcome. Clin Electroencephalogr. 1995;26:7683.Google Scholar
127.Cook, IA, Leuchter, AF, Witte, E, et al.Neurophysiologic predictors of treatment response to fluoxetine in major depression. Psychiatry Res. 1999;85:263273.Google Scholar
128.Leuchter, AF, Cook, IA, Lufkin, RB, et al.Cordance: a new method for assessment of cerebral perfusion and metabolism using quantitative electroencephalography. Neuroimage. 1994;1:208219.Google Scholar
129.Leuchter, AF, Cook, IA, Mena, I, et al.Assessment of cerebral perfusion using quantitative EEG cordance. Psychiatry Res. 1994;55:141152.Google Scholar
130.Leuchter, AF, Uijtdehaage, SH, Cook, IA, O'Hara, R, Mandelkern, M. Relationship between brain electrical activity and cortical perfusion in normal subjects. Psychiatry Res. 1999;90:125140.Google Scholar
131.Cook, IA, Leuchter, AF, Witte, E, et al.Neurophysiologic predictors of treatment response to fluoxetine in major depression. Psychiatry Res. 1999;85:263273.Google Scholar
132.Cook, IA, Leuchter, AF. Prefrontal changes and treatment response prediction in depression. Semin Clin Neuropsychiatry. 2001;6:113120.Google Scholar
133.Leuchter, AF, Cook, IA, Uijtdehaage, SH, et al.Brain structure and function and the outcomes of treatment for depression [published erratum appears in J Clin Psychiatry. 1998:5932]. J Clin Psychiatry. 1997;58(suppl 16):2231.Google Scholar
134.Cook, IA, Leuchter, AF, Morgan, ML, Stubbeman, W, Siegman, B, Abrams, M. Changes in prefrontal activity characterize clinical response in SSRI nonresponders: a pilot study. J Psychiatr Res. 2005;39:461466.Google Scholar
135.Leuchter, AF, Cook, IA, Witte, EA, Morgan, M, Abrams, M. Changes in brain function of depressed subjects during treatment with placebo. Am J Psychiatry. 2002;159:122129.Google Scholar
136.Kemp, AH, Silberstein, RB, Armstrong, SM, Nathan, PJ. Gender differences in the cortical electro-physiological processing of visual emotional stimuli. Neuroimage. 2004;21:632646.Google Scholar
137.Diego, MA, Field, T, Hernandez-Reif, M. CES-D depression scores are correlated with frontal EEG alpha asymmetry. Depress Anxiety. 2001;13:3237.Google Scholar
138.Davidson, RJ, Tomarken, AJ. Laterality and emotion: An electrophysiological approach. In: Boller, F, Grafman, J, eds. Handbook of Neuropsychology. vol 3. Amsterdam, the Netherlands: Elsevier; 1989:419441.Google Scholar
139.Mathersul, D, Williams, LM, Hopkinson, PJ, Kemp, AH. Investigating models of affect: relationships among EEG alpha asymmetry, depression, and anxiety. Emotion. 2008;8:560572.Google Scholar
140.Reid, SA, Duke, LM, Allen, JJ. Resting frontal electroencephalographic asymmetry in depression: inconsistencies suggest the need to identify mediating factors. Psychophysiology. 1998;35:389404.Google Scholar
141.Minnix, JA, Kline, JP, Blackhart, GC, Pettit, JW, Perez, M, Joiner, TE. Relative left-frontal activity is associated with increased depression in high reassurance-seekers. Biol Psychol. 2004;67:145155.Google Scholar
142.Bruder, GE, Stewart, JW, Tenke, CE, et al.Electroencephalographic and perceptual asymmetry differences between responders and nonresponders to an SSRI antidepressant. Biol Psychiatry. 2001;49:416425.Google Scholar
143.Hegerl, U, Juckel, G. Intensity dependence of auditory evoked potentials as an indicator of central serotonergic neurotransmission: a new hypothesis. Biol Psychiatry. 1993;33:173187.Google Scholar
144.Mulert, C, Juckel, G, Augustin, H, Hegerl, U. Comparison between the analysis of the loudness dependency of the auditory N1/P2 component with LORETA and dipole source analysis in the prediction of treatment response to the selective serotonin reuptake inhibitor citalopram in major depression. Clin Neurophysiol. 2002;113:15661572.Google Scholar
145.Paige, SR, Fitzpatrick, DF, Kline, JP, Balogh, SE, Hendricks, SE. Event-related potential amplitude/intensity slopes predict response to antidepressants. Neuropsychobiology. 1994;30:197201.Google Scholar
146.Linka, T, Muller, BW, Bender, S, Sartory, G, Gastpar, M. The intensity dependence of auditory evoked ERP components predicts responsiveness to reboxetine treatment in major depression. Pharmacopsychiatry. 2005;38:139143.Google Scholar
147.Nathan, PJ, Segrave, R, Phan, KL, O'Neill, B, Croft, RJ. Direct evidence that acutely enhancing serotonin with the selective serotonin reuptake inhibitor citalopram modulates the loudness dependence of the auditory evoked potential (LDAEP) marker of central serotonin function. Hum Psychopharmacol. 2006;21:4752.Google Scholar
148.Paige, SR, Hendricks, SE, Fitzpatrick, DF, Balogh, S, Burke, WJ. Amplitude/intensity functions of auditory event-related potentials predict responsiveness to bupropion in major depressive disorder. Psychopharmacol Bull. 1995;31:243248.Google Scholar
149.Nathan, PJ, O'Neill, B, Croft, RJ. Is the loudness dependence of the auditory evoked potential a sensitive and selective in vivo marker of central serotonergic function? Neuropsychopharmacology. 2005;30:15841585; author reply 1586-1587.Google Scholar
150.Bruder, GE, Tenke, CE, Stewart, JW, et al.Brain event-related potentials to complex tones in depressed patients: relations to perceptual asymmetry and clinical features. Psychophysiology. 1995;32:373381.Google Scholar
151.Bruder, GE, Tenke, CE, Stewart, JW, McGrath, PJ, Quitkin, FM. Predictors of therapeutic response to treatments for depression: a review of electrophysiologic and dichotic listening studies. CNS Spectr. 1999;4:3036.Google Scholar
152.Kalayam, B, Alexopoulos, GS. Prefrontal dysfunction and treatment response in geriatric depression. Arch Gen Psychiatry. 1999;56:713718.Google Scholar
153.Drevets, WC. Prefrontal cortical-amygdalar metabolism in major depression. Ann N Y Acad Sci. 1999;877:614637.Google Scholar
154.Wu, JC, Buchsbaum, M, Bunney, WE Jr. Clinicai neurochemical implications of sleep deprivation's effects on the anterior cingulate of depressed responders. Neuropsychopharmacology. 2001;25(suppl):s74s78.Google Scholar
155.Dougherty, DD, Rauch, SL. Brain correlates of antidepressant treatment outcome from neuroimaging studies in depression. Psychiatr Clin North Am. 2007;30:91103.Google Scholar
156.Mayberg, HS. Modulating dysfunctional limbic-cortical circuits in depression: towards development of brain-based algorithms for diagnosis and optimised treatment. Br Med Bull. 2003;65:193207.Google Scholar
157.Drevets, WC. Neuroimaging studies of mood disorders. Biol Psychiatry. 2000;48:813829.Google Scholar
158.Mayberg, HS, Liotti, M, Brannan, SK, et al.Reciprocal limbic-cortical function and negative mood: converging PET findings in depression and normal sadness. Am J Psychiatry. 1999;156:675682.Google Scholar
159.Wu, J, Buchsbaum, MS, Gillin, JC, et al.Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulate and medial prefrontal cortex. Am J Psychiatry. 1999;156:11491158.Google Scholar
160.Brody, AL, Saxena, S, Silverman, DH, et al.Brain metabolic changes in major depressive disorder from pre-to post-treatment with paroxetine. Psychiatry Res. 1999;91:127139.Google Scholar
161.Ebert, D, Feistel, H, Barocka, A, Kaschkfl, W. Increased limbic blood flow and total sleep depriva-tion in major depression with melancholia. Psychiatry Res. 1994;55:101109.Google Scholar
162.Wu, JC, Gillin, JC, Buchsbaum, MS, Hershey, T, Johnson, JC, Bunney, WE Jr. Effect of sleep deprivation on brain metabolism of depressed patients. Am J Psychiatry. 1992;149:538543.Google Scholar
163.Chen, CH, Ridler, K, Suckling, J, et al.Brain imaging correlates of depressive symptom severity and predictors of symptom improvement after antidepressant treatment. Biol Psychiatry. 2007;62:407–41.Google Scholar
164.Fu, CH, Williams, SC, Cleare, AJ, et al.Attenuation of the neural response to sad faces in major depression by antidepressant treatment: a prospective, event-related functional magnetic reso-nance imaging study. Arch Gen Psychiatry. 2004;61:877889.Google Scholar
165.Siegle, GJ, Carter, CS, Thase, ME. Use of FMRI to predict recovery from unipolar depression with cognitive behavior therapy. Am J Psychiatry. 2006;163:735738.Google Scholar
166.Devinsky, O, Morrell, MJ, Vogt, BA. Contributions of anterior cingulate cortex to behaviour. Brain. 1995;118(pt 1):279306.Google Scholar
167.Bush, G, Luu, P, Posner, MI. Cognitive and emotional influences in anterior cingulate cortex. Trends Cogn Sci. 2000;4:215222.Google Scholar
168.Mayberg, HS, Lozano, AM, Voon, V, et al.Deep brain stimulation for treatment-resistant depression. Neuron. 2005;45:651660.Google Scholar
169.Johansen-Berg, H, Gutman, DA, Behrens, TE, et al.Anatomical connectivity of the subgenual cingulate region targeted with deep brain stimulation for treatment-resistant depression. Cereb Cortex. 2008;18:13741383.Google Scholar
170.Fu, CH, Williams, SC, Brammer, MJ, et al.Neural responses to happy facial expressions in major depression following antidepressant treatment. Am J Psychiatry. 2007;164:599607.Google Scholar
171.Drevets, WC, Price, JL, Furey, ML. Brain structural and functional abnormalities in mood disorders: implications for neurocircuitry models of depression. Brain Struct Funct. 2008;213:93118.Google Scholar
172.Sheline, YI, Barch, DM, Donnelly, JM, Ollinger, JM, Snyder, AZ, Mintun, MA. Increased amygdala response to masked emotional faces in depressed subjects resolves with antidepressant treatment: an fMRI study. Biol Psychiatry. 2001;50:651658.Google Scholar
173.Robertson, B, Wang, L, Diaz, MT, et al.Effect of bupropion extended release on negative emotion processing in major depressive disorder: a pilot functional magnetic resonance imaging study. J Clin Psychiatry. 2007;68:261267.Google Scholar
174.Canli, T, Cooney, RE, Goldin, P, et al.Amygdala reactivity to emotional faces predicts improvement in major depression. Neuroreport. 2005;16:12671270.Google Scholar
175.Abercrombie, HC, Schaefer, SM, Larson, CL, et al.Metabolic rate in the right amygdala predicts negative affect in depressed patients. Neuroreport. 1998;9:33013307.Google Scholar
176.Drevets, WC, Videen, TO, Price, JL, Preskorn, SH, Carmichael, ST, Raichle, ME. A functional anatomical study of unipolar depression. J Neurosci. 1992;12:36283641.Google Scholar
177.Brody, AL, Saxena, S, Stoessel, P, et al.Regional brain metabolic changes in patients with major depression treated with either paroxetine or interpersonal therapy: preliminary findings. Arch Gen Psychiatry. 2001;58:631640.Google Scholar
178.Martin, SD, Martin, E, Rai, SS, Richardson, MA, Royall, R. Brain blood flow changes in depressed patients treated with interpersonal psychotherapy or venlafaxine hydrochloride: preliminary findings. Arch Gen Psychiatry. 2001;58:641648.Google Scholar
179.Goldapple, K, Segal, Z, Garson, C, et al.Modulation of cortical-limbic pathways in major depression: treatment-specific effects of cognitive behavior therapy. Arch Gen Psychiatry. 2004;61:3441.Google Scholar
180.Kennedy, SH, Konarski, JZ, Segal, ZV, et al.Differences in brain glucose metabolism between responders to CBT and venlafaxine in a 16-week randomized controlled trial. Am J Psychiatry. 2007;164:778788.Google Scholar
181.Little, JT, Ketter, TA, Kimbrell, TA, et al.Bupropion and venlafaxine responders differ in pretreatment regional cerebral metabolism in unipolar depression. Biol Psychiatry. 2005;57:220228.Google Scholar
182.Pillay, SS, Yurgelun-Todd, DA, Bonello, CM, Lafer, B, Fava, M, Renshaw, PF. A quantitative magnetic resonance imaging study of cerebral and cerebellar gray matter volume in primary unipolar major depression: relationship to treatment response and clinical severity. Biol Psychiatry. 1997;42:7984.Google Scholar
183.Rogers, MA, Bradshaw, JL, Pantelis, C, Phillips, JG. Frontostriatal deficits in unipolar major depression. Brain Res Bull. 1998;47:297310.Google Scholar
184.Sheline, YI, Gado, MH, Kraemer, HC. Untreated depression and hippocampal volume loss. Am J Psychiatry. 2003;160:15161518.Google Scholar
185.Campbell, S, Marriott, M, Nahmias, C, MacQueen, GM. Lower hippocampai volume in patients suffering from depression: a meta-analysis. Am J Psychiatry. 2004;161:598607.Google Scholar
186.Videbech, P, Ravnkilde, B. Hippocampal volume and depression: a meta-analysis of MRI studies. Am J Psychiatry. 2004;161:19571966.Google Scholar
187.Dranovsky, A, Hen, R. Hippocampal neurogenesis: regulation by stress and antidepressants. Biol Psychiatry. 2006;59:11361143.Google Scholar
188.Shah, PJ, Ebmeier, KP, Glabus, MF, Goodwin, GM. Cortical grey matter reductions associated with treatment-resistant chronic unipolar depression. Controlled magnetic resonance imaging study. Br J Psychiatry. 1998;172:527532.Google Scholar
189.Hsieh, MH, McQuoid, DR, Levy, RM, Payne, ME, MacFall, JR, Steffens, DC. Hippocampal volume and antidepressant response in geriatric depression. Int J Geriatr Psychiatry. 2002;17:519525.Google Scholar
190.Malhotra, AK, Murphy, GM Jr., Kennedy, JL. Pharmacogenetics of psychotropic drug response. Am J Psychiatry. 2004;161(5):780796.Google Scholar
191.Serretti, A, Artioli, P. From molecular biology to pharmacogenetics: a review of the literature on antidepressant treatment and suggestions of possible candidate genes. Psychopharmacology (Berl). 2004;174:490503.Google Scholar
192.Steimer, W, Muller, B, Leucht, S, Kissling, W. Pharmacogenetics: a new diagnostic tool in the management of antidepressive drug therapy. Clin Chim Acta. 2001;308:3341.Google Scholar
193.Binder, EB, Holsboer, F. Pharmacogenomics and antidepressant drugs. Ann Med. 2006;38:8294.Google Scholar
194.Lee, MS. Role of genetic polymorphisms related to neurotransmitters and cytochrome P-450 enzymes in response to antidepressants. Drugs Today (Barc). 2007;43:569581.Google Scholar
195.Charney, DS. Monoamine dysfunction and the pathophysiology and treatment of depression. J Clin Psychiatry. 1998;59:1114.Google Scholar
196.Schildkraut, JJ. The catecholamine hypothesis of affective disorders: a review of supporting evidence. Am JPsychiatry. 1965;122:509522.Google Scholar
197.Hindmarch, I. Expanding the horizons of depression: beyond the monoamine hypothesis. Hum Psychopharmacol. 2001;16:203218.Google Scholar
198.Wong, ML, O'Kirwan, F, Hannestad, JP, Irizarry, KJ, Elashoff, D, Licinio, J. St John's wort and imipramine-induced gene expression profiles identify cellular functions relevant to antidepressant action and novel pharmacogenetic candidates for the phenotype of antidepressant treatment response. Mol Psychiatry. 2004;9:237251.Google Scholar
199.Duman, RS, Monteggia, LM. A neurotrophic model for stress-related mood disorders. Biol Psychiatry. 2006;59:11161127.Google Scholar
200.Malberg, JE, Blendy, JA. Antidepressant action: to the nucleus and beyond. Trends Pharmacol Sci. 2005;26:631638.Google Scholar
201.Sapolsky, RM. Is impaired neurogenesis relevant to the affective symptoms of depression? Biol Psychiatry. 2004;56:137139.Google Scholar
202.Gold, PW, Chrousos, GP. Organization of the stress system and its dysregulation in melancholic and atypical depression: high vs low CRH/NE states. Mol Psychiatry. 2002;7:254275.Google Scholar
203.Holsboer, F. The corticosteroid receptor hypothesis of depression. Neuropsychopharmacology. 2000;23:477501.Google Scholar
204.Neigh, GN, Nemeroff, CB. Reduced glucocorticoid receptors: consequence or cause of depression? Trends Endocrinol Metab. 2006;17:124125.Google Scholar
205.McMahon, FJ, Buervenich, S, Charney, D, et al.Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment. Am J Hum Genet. 2006;78(5):804814.Google Scholar
206.Ohara, K, Nagai, M, Suzuki, Y, Yoshida, K, Tsukamoto, T, Ohara, K. Apolipoprotein E epsilon 4 allele and Japanese late-onset depressive disorders. Biol Psychiatry. 1999;45:308312.Google Scholar
207.Ohara, K, Suzuki, Y, Yoshida, K, Terada, H, Ohara, K. Lack of association between alphai-antichymotrypsin polymorphism and late-onset depressive disorder. Psychiatry Res. 1999;88:221226.Google Scholar
208.Brouwer, JP, Appelhof, BC, Peeters, RP, et al.Thyrotropin, but not a polymorphism in type II deiodinase, predicts response to paroxetine in major depression. Eur J Endocrinol. 2006;154:819825.Google Scholar
209.Smits, KM, Smits, LJ, Schouten, JS, Stelma, FF, Nelemans, P, Prins, MH. Influence of SERTPR and STin2 in the serotonin transporter gene on the effect of selective serotonin reuptake inhibitors in depression: a systematic review. Mol Psychiatry. 2004;9:433441.Google Scholar
210.Smeraldi, E, Serretti, A, Artioli, P, Lorenzi, C, Catalano, M. Serotonin transporter gene-linked polymorphic region: possible pharmacogenetic implications of rare variants. Psychiafr Genet. 2006;16:153158.Google Scholar
211.Smeraldi, E, Zanardi, R, Benedetti, F, Di Bella, D, Perez, J, Catalano, M. Polymorphism within the promoter of the serotonin transporter gene and antidepressant efficacy of fluvoxamine. Mol Psychiatry. 1998;3:508511.Google Scholar
212.Pollock, BG, Ferrell, RE, Mulsant, BH, et al.Allelic variation in the serotonin transporter promoter affects onset of paroxetine treatment response in late-life depression. Neuropsychopharmacology. 2000;23:587590.Google Scholar
213.Zanardi, R, Benedetti, F, Di Bella, D, Catalano, M, Smeraldi, E. Efficacy of paroxetine in depression is influenced by a functional polymorphism within the promoter of the serotonin transporter gene. J Clin Psychopharmacol. Feb 2000;20:105107.Google Scholar
214.Kato, M, Fukuda, T, Wakeno, M, et al.Effects of the serotonin type 2A, 3A and 3B receptor and the serotonin transporter genes on paroxetine and fluvoxamine efficacy and adverse drug reactions in depressed Japanese patients. Neuropsychobiology. 2006;53:186195.Google Scholar
215.Kim, DK, Lim, SW, Lee, S, et al.Serotonin transporter gene polymorphism and antidepressant response. Neuroreport. 2000;11:215219.Google Scholar
216.Yoshida, K, Ito, K, Sato, K, et al.Influence of the serotonin transporter gene-linked polymorphic region on the antidepressant response to fluvoxamine in Japanese depressed patients. Prog Neuropsychopharmacol Biol Psychiatry. 2002;26:383386.Google Scholar
217.Kim, H, Lim, SW, Kim, S, et al.Monoamine transporter gene polymorphisms and antidepressant response in koreans with late-life depression. JAMA. 2006;296:16091618.Google Scholar
218.Hu, XZ, Rush, AJ, Chamey, D, et al.Association between a functional serotonin transporter promoter polymorphism and citalopram treatment in adult outpatients with rrtajor depression. Arch Gen Psychiatry. 2007;64:783792.Google Scholar
219.Hu, XZ, Lipsky, RH, Zhu, G, et al.Serotonin transporter promoter gain-of-function genotypes are linked to obsessive-compulsive disorder. Am J Hum Genet. 2006;78:815826.Google Scholar
220.Mandelli, L, Marino, E, Pirovano, A, et al.Interaction between SERTPR and stressful life events on response to antidepressant treatment. Eur Neuropsychopharmacol. September 22 2008. [Epub ahead of print].Google Scholar
221.Yoshida, K, Takahashi, H, Higuchi, H, et al.Prediction of antidepressant response to milnacipran by norepinephrine transporter gene polymorphisms. Am J Psychiatry. 2004;161:15751580.Google Scholar
222.Kirchheiner, J, Nickchen, K, Sasse, J, Bauer, M, Roots, I, Brockmoller, J. A 40-basepair VNTR polymorphism in the dopamine transporter (DAT1) gene and the rapid response to antidepressant treatment. Pharmacogenomics J. 2007;7:4855.Google Scholar
223.Yoshida, K, Higuchi, H, Takahashi, H, et al.Influence of the tyrosine hydroxylase val81met polymorphism and catechol-O-methyltransferase val158met polymorphism on the antidepressant effect of milnacipran. Hum Psychopharmacol. 2008;23:121128.Google Scholar
224.Szegedi, A, Rujescu, D, Tadic, A, et al.The catechol-O-methyltransferase Val108/158Met polymorphism affects short-term treatment response to mirtazapine, but not to paroxetine in major depression. Pharmacogenomics J. 2005;5:4953.Google Scholar
225.Tadic, A, Muller, MJ, Rujescu, D, et al.The MAOA T941G polymorphism and short-term treatment response to mirtazapine and paroxetine in major depression. Am J Med Genet B Neuropsychiatr Genet. 2007;144B:325331.Google Scholar
226.Tadic, A, Rujescu, O, Muller, MJ, et al.A monoamine oxidase B gene variant and short-term antidepressant treatment response. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31:13701377.Google Scholar
227.Egan, MF, Kojima, M, Callicott, JH, et al.The BDNF val66met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell. 2003;112:257269.Google Scholar
228.Chen, ZY, Jing, D, Bath, KG, et al.Genetic variant BDNF (Val66Met) polymorphism alters anxiety-related behavior. Science. 2006;314:140143.Google Scholar
229.Tsai, SJ, Cheng, CY, Yu, YW, Chen, TJ, Hong, CJ. Association study of a brain-derived neurotrophic-factor genetic polymorphism and major depressive disorders, symptomatology, and antidepressant response. Am J Med Genet B Neuropsychiatr Genet. 2003;123:1922.Google Scholar
230.Choi, MJ, Kang, RH, Lim, SW, Oh, KS, Lee, MS. Brain-derived neurotrophic factor gene polymorphism (Val66Met) and citalopram response in major depressive disorder. Brain Res. 2006;1118:176182.Google Scholar
231.Yoshida, K, Higuchi, H, Kamata, M, et al.The G196A polymorphism of the brain-derived neurotrophic factor gene and the antidepressant effect of milnacipran and fluvoxamine. J Psychopharmacol. 2007;21:650656.Google Scholar
232.Comings, DE, MacMurray, JP. Molecular heterosis: a review. Mol Genet Metab. 2000;71:1931.Google Scholar
233.Brouwer, JP, Appelhof, BC, van Rossum, EF, et al.Prediction of treatment response by HPA-axis and gluco-corticoid receptor polymorphisms in major depression. Psychoneuroendocrinology. 2006;31:11541163.Google Scholar
234.Kato, M, Fukuda, T, Serretti, A, et al.ABCB1 (MDR1) gene polymorphisms are associated with the clinical response to paroxetine in patients with major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2008;32:398404.Google Scholar
235.Mihaljevic Peles, A, Bozina, N, Sagud, M, Rojnic Kuzman, M, Lovric, M. MDR1 gene polymorphism: therapeutic response to paroxetine among patients with major depression. Prog Neuropsychopharmacol Biol Psychiatry. 2008;32:14391444.Google Scholar
236.Scargle, J. Publication Bias: the “File-Drawer Problem” in scientific inference. Journal for Scientific Exploration. 2000;14:91106.Google Scholar
237.Rosenthal, R. The file drawer problem and tolerance for null results. Psychiatr Bull. 1979;86:638641.Google Scholar
238.Gordon, E, Liddell, BJ, Brown, KJ, et al.Integrating objective gene-brain-behavior markers of psychiatric disorders. J Integr Neurosci. 2007;6:134.Google Scholar
239.Gordon, E, Cooper, N, Rennie, C, Hermens, D, Williams, LM. Integrative neuroscience: the role of a standardized database. Clin EEG Neurosci. 2005;36:6475.Google Scholar
240.Gordon, E, Barnett, KJ, Cooper, NJ, Tran, N, Williams, LM. An integrative neuroscience platform: application to profiles of negativity and positivity bias. Journal of Integrative Neuroscience. 2008;7:122.Google Scholar
241.Gordon, E. Genomics and Neuromarkers are both required for the era of brain-related “Personalized Medicine.” Personalized Medicine. 2007;4:201215.Google Scholar
242.Simons, AD, Gordon, JS, Monroe, SM, Thase, ME. Toward an integration of psychologic, social, and biologic factors in depression: effects on outcome and course of cognitive therapy. J Consult Clin Psychol. 1995;63:369377.Google Scholar
243.Leuchter, AF, Morgan, M, Cook, IA, Dunkin, J, Abrams, M, Witte, E. Pretreatment neurophysiological and clinical characteristics of placebo responders in treatment trials for major depression. Psychopharmacology (Berl). 2004;177:1522.Google Scholar
244.Williams, LM, Gatt, JM, Hatch, A, et al.The INTEGRATE model of emotion, thinking and self regulation: an application to the “Paradox of Aging.” J Integr Neurosci. 2008;7:367404.Google Scholar
245.Williams, LM, Phillips, ML, Brammer, MJ, et al.Arousal dissociates amygdala and hippocampal fear responses: evidence from simultaneous fMRI and skin conductance recording. Neuroimage. 2001;14:10701079.Google Scholar
246.Sartorius, N, Ustun, TB, Lecrubier, Y, Wittchen, HU. Depression comorbid with anxiety: results from the WHO study on psychological disorders in primary health care. Br J Psychiatry Suppl. 1996:3843.Google Scholar
247.Hariri, AR, Lewis, DA. Genetics and the future of clinical psychiatry. Am J Psychiatry. 2006;163:16761678.Google Scholar
248.Hariri, AR, Weinberger, DR. Imaging genomics. Br Med Bull. 2003;65:259270.Google Scholar
249.Hariri, AR, Mattay, VS, Tessitore, A, et al.Serotonin transporter genetic variation and the response of the human amygdala. Science. 2002;297:400403.Google Scholar
250.Pezawas, L, Meyer-Lindenberg, A, Drabant, EM, et al.5-HTTLPR polymorphism impacts human cingulateamygdala interactions: a genetic susceptibility mechanism for depression. Nat Neurosci. 2005;8:828834.Google Scholar
251.Hariri, AR, Drabant, EM, Munoz, KE, et al.A susceptibility gene for affective disorders and the response of the human amygdala. Arch Gen Psychiatry. 2005;62:146152.Google Scholar
252.Hong, CJ, Huo, SJ, Yen, FC, Tung, CL, Pan, GM, Tsai, SJ. Association study of a brain-derived neurotrophic-factor genetic polymorphism and mood disorders, age of onset and suicidal behavior. Neuropsychobiology. 2003;48:186189.Google Scholar
253.Oswald, P. Del-Favero, J, Massat, I, et al.No implication of brain-derived neurotrophic factor (BDNF) gene in unipolar affective disorder: evidence from Belgian first and replication patient-control studies. Eur Neuropsychopharmacol. 2005;15:491495.Google Scholar
254.Gatt, JM, Clark, CR, Kemp, AH, et al.A genotype-endophenotype-phenotype path model of depressed mood: integrating cognitive and emotional markers. J Integr Neurosci. 2007;6:75104.Google Scholar
255.Gatt, JM, Kuan, SA, Dobson-Stone, C, et al.Association between BDNF Val66Met polymorphism and trait depression is mediated via resting EEG alpha band activity. Biol Psychol. 2008;79:275284.Google Scholar
256.Gottesman, II, Gould, TD. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry. 2003;160:636645.Google Scholar
257.Gould, TD, Gottesman, II. Psychiatric endophenotypes and the development of valid animal models. Genes Brain Behav. 2006;5:113119.CrossRefGoogle ScholarPubMed
258.Corder, EH, Saunders, AM, Strittmatter, WJ, et al.Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer's disease in late onset families. Science. 1993;261:921923.Google Scholar
259.Alexander, DM, Williams, LM, Gatt, JM, et al.The contribution of apolipoprotein E alleles on cognitive performance and dynamic neural activity over six decades. Biol Psychol. 2007;75:229238.Google Scholar
260.Egan, MF, Goldberg, TE, Kolachana, BS, et al.Effect of COMT Val108/158 Met genotype on frontal lobe function and risk for schizophrenia. Proc Natl Acad Sci U S A. 2001;98:69176922.Google Scholar
261.Hariri, AR, Weinberger, DR. Functional neuroimaging of genetic variation in serotonergic neurotransmission. Genes Brain Behav. 2003;2:341349.Google Scholar
262.WMA. Declaration of Helsinki: Ethical Principles for Medical Research Involving Human Subjects. October 2008. Available at: http://www.wma.net/e/policy/b3.htm. Accessed November, 2008.Google Scholar
263.Amsterdam, JD, Hornig, M, Nirenberg, AA. Treatment-Resistant Mood Disorders. Cambridge, UK: Cambridge University Press; 2001.Google Scholar
264.Bagby, RM, Ryder, AG, Schuller, DR, Marshall, MB. The Hamilton Depression Rating Scale: has the gold standard become a lead weight? Am J Psychiatry. 2004;161:21632177.Google Scholar
265.Hasler, G, Drevets, WC, Manji, HK, Charney, DS. Discovering endophenotypes for major depression. Neuropsychopharmacology. 2004;29:17651781.Google Scholar