Abstract
Major depressive disorder leads to substantial individual and socioeconomic costs. Despite the ongoing efforts to improve the treatment for this condition, a trial-and-error approach until an individually effective treatment is established still dominates clinical practice. Searching for clinically useful treatment response predictors is one of the most promising strategies to change this quandary therapeutic situation. This study evaluated the predictive value of a biological and a clinical predictor, as well as a combination of both. Pretreatment EEGs of 31 patients with a major depressive episode were analyzed with neuroelectric brain imaging technique to assess cerebral oscillations related to treatment response. Early improvement of symptoms served as a clinical predictor. Treatment response was assessed after 4 weeks of antidepressant treatment. Responders showed more slow-frequency power in the right anterior cingulate cortex compared to non-responders. Slow-frequency power in this region was found to predict response with good sensitivity (82 %) and specificity (100 %), while early improvement showed lower accuracy (73 % sensitivity and 65 % specificity). Combining both parameters did not further improve predictive accuracy. Pretreatment activity within the anterior cingulate cortex is related to antidepressive treatment response. Our results support the search for biological treatment response predictors using electric brain activity. This technique is advantageous due to its low individual and socioeconomic burden. The benefits of combining both, a clinically and a biologically based predictor, should be further evaluated using larger sample sizes.
Similar content being viewed by others
References
Bauer M, Pfennig A, Linden M, Smolka MN, Neu P, Adli M (2009) Efficacy of an algorithm-guided treatment compared with treatment as usual: a randomized, controlled study of inpatients with depression. J Clin Psychopharmacol 29:327–333
van Calker D, Zobel I, Dykierek P, Deimel CM, Kech S, Lieb K et al (2009) Time course of response to antidepressants: predictive value of early improvement and effect of additional psychotherapy. J Affect Disord 114:243–253
Henkel V, Seemuller F, Obermeier M, Adli M, Bauer M, Mundt C et al (2009) Does early improvement triggered by antidepressants predict response/remission? Analysis of data from a naturalistic study on a large sample of inpatients with major depression. J Affect Disord 115:439–449
Szegedi A, Jansen WT, van Willigenburg AP, van der Meulen E, Stassen HH, Thase ME (2009) Early improvement in the first 2 weeks as a predictor of treatment outcome in patients with major depressive disorder: a meta-analysis including 6562 patients. J Clin Psychiatry 70:344–353
Stamm TJ, Adli M, Kirchheiner J, Smolka MN, Kaiser R, Tremblay PB et al (2008) Serotonin transporter gene and response to lithium augmentation in depression. Psychiatr Genet 18:92–97
Adli M, Hollinde DL, Stamm T, Wiethoff K, Tsahuridu M, Kirchheiner J et al (2007) Response to lithium augmentation in depression is associated with the glycogen synthase kinase 3-beta -50T/C single nucleotide polymorphism. Biol Psychiatry 62:1295–1302
Bruder GE, Sedoruk JP, Stewart JW, McGrath PJ, Quitkin FM, Tenke CE (2008) Electroencephalographic alpha measures predict therapeutic response to a selective serotonin reuptake inhibitor antidepressant: pre- and post-treatment findings. Biol Psychiatry 63:1171–1177
Gallinat J, Bottlender R, Juckel G, Munke-Puchner A, Stotz G, Kuss HJ et al (2000) The loudness dependency of the auditory evoked N1/P2-component as a predictor of the acute SSRI response in depression. Psychopharmacology 148:404–411
Lee TW, Wu YT, Yu YW, Chen MC, Chen TJ (2011) The implication of functional connectivity strength in predicting treatment response of major depressive disorder: a resting EEG study. Psychiatry Res 194:372–377
Hunter AM, Cook IA, Leuchter AF (2007) The promise of the quantitative electroencephalogram as a predictor of antidepressant treatment outcomes in major depressive disorder. Psychiatr Clin North Am 30:105–124
Alhaj H, Wisniewski G, McAllister-Williams RH (2011) The use of the EEG in measuring therapeutic drug action: focus on depression and antidepressants. J. Psychopharmacol 25:1175–1191
Kemp AH, Gordon E, Rush AJ, Williams LM (2008) Improving the prediction of treatment response in depression: integration of clinical, cognitive, psychophysiological, neuroimaging, and genetic measures. CNS Spectr 13:1066–1086
Leuchter AF, Cook IA, Hamilton SP, Narr KL, Toga A, Hunter AM et al (2010) Biomarkers to predict antidepressant response. Curr Psychiatry Rep 12:553–562
Pizzagalli DA (2011) Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology 36:183–206
Gallinat J, Gotz T, Kalus P, Bajbouj M, Sander T, Winterer G (2007) Genetic variations of the NR3A subunit of the NMDA receptor modulate prefrontal cerebral activity in humans. J Cogn Neurosci 19:59–68
Pizzagalli D, Pascual-Marqui RD, Nitschke JB, Oakes TR, Larson CL, Abercrombie HC et al (2001) Anterior cingulate activity as a predictor of degree of treatment response in major depression: evidence from brain electrical tomography analysis. Am J Psychiatry 158:405–415
Korb AS, Hunter AM, Cook IA, Leuchter AF (2009) Rostral anterior cingulate cortex theta current density and response to antidepressants and placebo in major depression. Clin Neurophysiol 120:1313–1319
Mulert C, Juckel G, Brunnmeier M, Karch S, Leicht G, Mergl R et al (2007) Prediction of treatment response in major depression: integration of concepts. J Affect Disord 98:215–225
Ackenheil M, Stotz G, Dietz-Bauer R, Vossen A (1999) M. I. N. I. Mini International Neuropsychiatric Interview. Psychiatrische Universitätsklinik München, Germany
Pascual-Marqui RD (2002) Standardized low-resolution brain electromagnetic tomography (sLORETA): technical details. Methods Find Exp Clin Pharmacol 24(Suppl D):5–12
Nichols TE, Holmes AP (2002) Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 15:1–25
Fawcett T (2006) An introduction to ROC analysis. Pattern Recogn Lett 27:861–874
Fitzgerald PB, Laird AR, Maller J, Daskalakis ZJ (2008) A meta-analytic study of changes in brain activation in depression. Hum Brain Mapp 29:683–695
Gemar MC, Segal ZV, Mayberg HS, Goldapple K, Carney C (2007) Changes in regional cerebral blood flow following mood challenge in drug-free, remitted patients with unipolar depression. Depress Anxiety 24:597–601
Kühn S and Gallinat J (2013) Resting-state brain activity in schizophrenia and major depression: a quantitative meta-analysis. Schizophr Bull 39:358–365
Clark CP, Brown GG, Frank L, Thomas L, Sutherland AN, Gillin JC (2006) Improved anatomic delineation of the antidepressant response to partial sleep deprivation in medial frontal cortex using perfusion-weighted functional MRI. Psychiatry Res 146:213–222
Davidson RJ, Irwin W, Anderle MJ, Kalin NH (2003) The neural substrates of affective processing in depressed patients treated with venlafaxine. Am J Psychiatry 160:64–75
Ebert D, Feistel H, Barocka A (1991) Effects of sleep deprivation on the limbic system and the frontal lobes in affective disorders: a study with Tc-99m-HMPAO SPECT. Psychiatry Res 40:247–251
Holthoff VA, Beuthien-Baumann B, Zundorf G, Triemer A, Ludecke S, Winiecki P et al (2004) Changes in brain metabolism associated with remission in unipolar major depression. Acta Psychiatr Scand 110:184–194
Konarski JZ, Kennedy SH, Segal ZV, Lau MA, Bieling PJ, McIntyre RS et al (2009) Predictors of nonresponse to cognitive behavioural therapy or venlafaxine using glucose metabolism in major depressive disorder. J Psychiatry Neurosci 34:175–180
Kozel FA, Rao U, Lu H, Nakonezny PA, Grannemann B, McGregor T et al (2011) Functional connectivity of brain structures correlates with treatment outcome in major depressive disorder. Front Psychiatry 2:1–7
Mayberg HS, Lozano AM, Voon V, McNeely HE, Seminowicz D, Hamani C et al (2005) Deep brain stimulation for treatment-resistant depression. Neuron 45:651–660
Roy M, Harvey PO, Berlim MT, Mamdani F, Beaulieu MM, Turecki G et al (2010) Medial prefrontal cortex activity during memory encoding of pictures and its relation to symptomatic improvement after citalopram treatment in patients with major depression. J Psychiatry Neurosci 35:152–162
Salvadore G, Cornwell BR, Sambataro F, Latov D, Colon-Rosario V, Carver F et al (2010) Anterior cingulate desynchronization and functional connectivity with the amygdala during a working memory task predict rapid antidepressant response to ketamine. Neuropsychopharmacology 35:1415–1422
Wu J, Buchsbaum MS, Gillin JC, Tang C, Cadwell S, Wiegand M et al (1999) Prediction of antidepressant effects of sleep deprivation by metabolic rates in the ventral anterior cingulate and medial prefrontal cortex. Am J Psychiatry 156:1149–1158
Mulert C, Juckel G, Brunnmeier M, Karch S, Leicht G, Mergl R et al (2007) Rostral anterior cingulate cortex activity in the theta band predicts response to antidepressive medication. Clin EEG Neurosci 38:78–81
Korb AS, Cook IA, Hunter AM, Leuchter AF (2008) Brain electrical source differences between depressed subjects and healthy controls. Brain Topogr 21:138–146
Armey MF, Fresco DM, Moore MT, Mennin DS, Turk CL, Heimberg RG et al (2009) Brooding and pondering: isolating the active ingredients of depressive rumination with exploratory factor analysis and structural equation modeling. Assessment 16:315–327
McVay JC, Kane MJ, Kwapil TR (2009) Tracking the train of thought from the laboratory into everyday life: an experience-sampling study of mind wandering across controlled and ecological contexts. Psychon Bull Rev 16:857–863
Kuehner C and Huffziger S (2012) Response styles to depressed mood affect the long-term course of psychosocial functioning in depressed patients. J Affect Disord 136:627–633
Watts FN, Sharrock R (1985) Description and measurement of concentration problems in depressed patients. Psychol Med 15:317–326
Kühn S, Vanderhasselt MA, De Raedt R, Gallinat J (2012) Why ruminators won’t stop: the structural and resting state correlates of rumination and its relation to depression. J Affect Disord 141:352–360
Mason MF, Norton MI, Van Horn JD, Wegner DM, Grafton ST, Macrae CN (2007) Wandering minds: the default network and stimulus-independent thought. Science 315:393–395
Hamilton JP, Furman DJ, Chang C, Thomason ME, Dennis E, Gotlib IH (2011) Default-mode and task-positive network activity in major depressive disorder: implications for adaptive and maladaptive rumination. Biol Psychiatry 70:327–333
Cooney RE, Joormann J, Eugene F, Dennis EL, Gotlib IH (2010) Neural correlates of rumination in depression. Cogn Affect Behav Neurosci 10:470–478
Johnson MK, Nolen-Hoeksema S, Mitchell KJ, Levin Y (2009) Medial cortex activity, self-reflection and depression. Soc Cogn Affect Neurosci 4:313–327
Ray RD, Ochsner KN, Cooper JC, Robertson ER, Gabrieli JD, Gross JJ (2005) Individual differences in trait rumination and the neural systems supporting cognitive reappraisal. Cogn Affect Behav Neurosci 5:156–168
Berman MG, Peltier S, Nee DE, Kross E, Deldin PJ, Jonides J (2011) Depression, rumination and the default network. Soc Cogn Affect Neurosci 6:548–555
Zhu X, Wang X, Xiao J, Liao J, Zhong M, Wang W et al (2012) Evidence of a dissociation pattern in resting-state default mode network connectivity in first-episode, treatment-naive major depression patients. Biol Psychiatry 71:611–617
Qin P, Northoff G (2011) How is our self related to midline regions and the default-mode network? Neuroimage 57:1221–1233
Travis F, Shear J (2010) Focused attention, open monitoring and automatic self-transcending: categories to organize meditations from Vedic, Buddhist and Chinese traditions. Conscious Cogn 19:1110–1118
Tei S, Faber PL, Lehmann D, Tsujiuchi T, Kumano H, Pascual-Marqui RD et al (2009) Meditators and non-meditators: EEG source imaging during resting. Brain Topogr 22:158–165
Taylor VA, Daneault V, Grant J, Scavone G, Breton E, Roffe-Vidal S et al (2013) Impact of meditation training on the default mode network during a restful state. Soc Cogn Affect Neurosci 8:4–14
Hlinka J, Alexakis C, Diukova A, Liddle PF, Auer DP (2010) Slow EEG pattern predicts reduced intrinsic functional connectivity in the default mode network: an inter-subject analysis. Neuroimage 53:239–246
Scheeringa R, Bastiaansen MC, Petersson KM, Oostenveld R, Norris DG, Hagoort P (2008) Frontal theta EEG activity correlates negatively with the default mode network in resting state. Int J Psychophysiol 67:242–251
van Aalderen JR, Donders AR, Giommi F, Spinhoven P, Barendregt HP, Speckens AE (2012) The efficacy of mindfulness-based cognitive therapy in recurrent depressed patients with and without a current depressive episode: a randomized controlled trial. Psychol Med 42:1–13
Watkins ER, Mullan E, Wingrove J, Rimes K, Steiner H, Bathurst N et al (2011) Rumination-focused cognitive-behavioural therapy for residual depression: phase II randomised controlled trial. Br J Psychiatry 199:317–322
Andersen SB, Moore RA, Venables L, Corr PJ (2009) Electrophysiological correlates of anxious rumination. Int J Psychophysiol 71:156–169
Abulseoud OA, Gitlin M, Altshuler L, Frye MA (2013) Baseline thyroid indices and the subsequent response to citalopram treatment, a pilot study. Brain Behav 3:89–94
Serretti A, Kato M, De Ronchi D, Kinoshita T (2007) Meta-analysis of serotonin transporter gene promoter polymorphism (5-HTTLPR) association with selective serotonin reuptake inhibitor efficacy in depressed patients. Mol Psychiatry 12:247–257
Jain FA, Hunter AM, Brooks JO 3rd, Leuchter AF (2013) Predictive socioeconomic and clinical profiles of antidepressant response and remission. Depress Anxiety 30:624–630
Trivedi MH, Rush AJ, Wisniewski SR, Nierenberg AA, Warden D, Ritz L, Norquist G, Howland RH, Lebowitz B, McGrath PJ, Shores-Wilson K, Biggs MM, Balasubramani GK, Fava M, STAR*D Study Team (2006) Evaluation of outcomes with citalopram for depression using measurement-based care in STAR*D: implications for clinical practice. Am J Psychiatry 163:28–40
Iosifescu DV, Greenwald S, Devlin P, Mischoulon D, Denninger JW, Alpert JE, Fava M (2009) Frontal EEG predictors of treatment outcome in major depressive disorder. Eur Neuropsychopharmacol 19:772–777
Walsh BT, Seidman SN, Sysko R, Gould M (2002) Placebo response in studies of major depression: variable, substantial, and growing. JAMA 287:1840–1847
Renoir T (2013) Selective serotonin reuptake inhibitor antidepressant treatment discontinuation syndrome: a review of the clinical evidence and the possible mechanisms involved. Front Pharmacol 4:1–10
Saletu B, Anderer P, Saletu-Zyhlarz GM (2006) EEG topography and tomography (LORETA) in the classification and evaluation of the pharmacodynamics of psychotropic drugs. Clin EEG Neurosci 37:66–80
National Collaborating Centre for Mental Health (UK) (2010) Depression: the treatment and management of depression in adults (updated edition). Leicester (UK): British psychological society. (NICE Clinical Guidelines, No. 90.) Available from: http://www.ncbi.nlm.nih.gov/books/NBK63748
Acknowledgments
J. R. received support from the NARSAD young investigator award 2009, National Alliance for Research on Schizophrenia and Depression.
Conflict of interest
None.
Author information
Authors and Affiliations
Corresponding author
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Rentzsch, J., Adli, M., Wiethoff, K. et al. Pretreatment anterior cingulate activity predicts antidepressant treatment response in major depressive episodes. Eur Arch Psychiatry Clin Neurosci 264, 213–223 (2014). https://doi.org/10.1007/s00406-013-0424-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00406-013-0424-1