Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-25T04:48:47.518Z Has data issue: false hasContentIssue false

Brain-Based Biomarkers for the Treatment of Depression: Evolution of an Idea

Published online by Cambridge University Press:  04 December 2017

Allison C. Waters*
Affiliation:
Emory University School of Medicine, Department of Psychiatry and Behavioral Sciences
Helen S. Mayberg
Affiliation:
Emory University School of Medicine, Department of Psychiatry and Behavioral Sciences
*
Correspondence and reprint requests to: Allison C. Waters, 101 Woodruff Circle, WMB 4205, Atlanta, GA 30303. E-mail: [email protected]

Abstract

An ambition of depression biomarker research is to augment psychometric and cognitive assessment of clinically relevant phenomena with neural measures. Although such applications have been slow to arrive, we observe a steady evolution of the idea and anticipate emerging technologies with some optimism. To highlight critical themes and innovations in depression biomarker research, we take as our point of reference a specific research narrative. We begin with an early model of frontal-limbic dysfunction, which represents a conceptual shift from localized pathology to understanding symptoms as an emergent property of distributed networks. Over the decades, this model accommodates perspectives from neurology, psychiatry, clinical, and cognitive neuroscience, and preserves past insight as more complex methods become available. We also track the expanding mission of brain biomarker research: from the development of diagnostic tools to treatment selection algorithms, measures of neurocognitive functioning and novel targets for neuromodulation. To conclude, we draw from this particular research narrative future directions for biomarker research. We emphasize integration of measurement modalities to describe dynamic change in domain-general networks, and we speculate that a brain-based framework for psychiatric problems may dissolve classical diagnostic and disciplinary boundaries. (JINS, 2017, 23, 870–880)

Type
Section 3 – Neuropsychiatric Disorders
Copyright
Copyright © The International Neuropsychological Society 2017 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alexander, G. E., DeLong, M.R., & Strick, P.L. (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience, 9(1), 357381.Google Scholar
Auerbach, R.P., Bondy, E., Stanton, C.H., Webb, C.A., Shankman, S.A., & Pizzagalli, D.A. (2016). Self-referential processing in adolescents: Stability of behavioral and ERP markers. Psychophysiology, 53(9), 13981406.Google Scholar
Baxter, L.R., Schwartz, J.M., Phelps, M.E., Mazziotta, J.C., Guze, B.H., Selin, C.E., & Sumida, R.M. (1989). Reduction of prefrontal cortex glucose metabolism common to three types of depression. Archives of General Psychiatry, 46(3), 243250.Google Scholar
Badcock, P.B., Davey, C.G., Whittle, S., Allen, N.B., & Friston, K.J. (2017). The depressed brain: An evolutionary systems theory. Trends in Cognitive Sciences, 21, 182194.Google Scholar
Blumer, D., & Benson, D.F. (1975). Personality changes with frontal and temporal lobe lesions Psychiatric aspects of neurologic disease (Vol. 1., pp. 151170). New York, New York: Grune & Stratton, Inc.Google Scholar
Chanes, L., & Barrett, L.F. (2016). Redefining the role of limbic areas in cortical processing. Trends in Cognitive Sciences, 20(2), 96106.Google Scholar
Crane, N.A., Jenkins, L.M., Bhaumik, R., Dion, C., Gowins, J.R., Mickey, B.J., & Langenecker, S.A. (2017). Multidimensional prediction of treatment response to antidepressants with cognitive control and functional MRI. Brain, 140(2), 472486.Google Scholar
Davidson, R.J., Irwin, W., Anderle, M.J., & Kalin, N.H. (2003). The neural substrates of affective processing in depressed patients treated with venlafaxine. The American Journal of Psychiatry, 160, 6475.Google Scholar
DeRubeis, R.J., Siegle, G.J., & Hollon, S.D. (2008). Cognitive therapy versus medication for depression: Treatment outcomes and neural mechanisms. Nature Reviews. Neuroscience, 9(10), 788796.Google Scholar
Drevets, W.C., Price, J.L., & Furey, M.L. (2008). Brain structural and functional abnormalities in mood disorders: Implications for neurocircuitry models of depression. Brain structure and function, 213(1-2), 93118.Google Scholar
Drevets, W.C., Price, J.L., Simpson, J.R. Jr., Todd, R.D., Reich, T., Vannier, M., & Raichle, M.E. (1997). Subgenual prefrontal cortex abnormalities in mood disorders. Nature, 386(6627), 824827.CrossRefGoogle ScholarPubMed
Dunlop, B.W., & Mayberg, H.S. (2014). Neuroimaging-based biomarkers for treatment selection in major depressive disorder. Dialogues in Clinical Neuroscience, 16(4), 479.Google Scholar
Dunlop, B.W., Rajendra, J.K., Craighead, W.E., Kelley, M.E., McGrath, C.L., Choi, K.S., & Mayberg, H.S. (2017). Functional connectivity of the subcallosal cingulate cortex and differential outcomes to treatment with cognitive-behavioral therapy or antidepressant medication or major depressive disorder. The American Jounal of Psychiatry, 174(6), 533545.Google Scholar
Farb, N.A., Segal, Z.V., Mayberg, H., Bean, J., McKeon, D., Fatima, Z., & Anderson, A.K. (2007). Attending to the present: Mindfulness meditation reveals distinct neural modes of self-reference. Social Cognitive and Affective Neuroscience, 2(4), 313322.Google Scholar
Fox, M.D., Buckner, R.L., White, M.P., Greicius, M.D., & Pascual-Leone, A. (2012). Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate. Biological Psychiatry, 72(7), 595603.Google Scholar
Fu, C.H., Steiner, H., & Costafreda, S.G. (2013). Predictive neural biomarkers of clinical response in depression: A meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiology of Disease, 52, 7583.CrossRefGoogle ScholarPubMed
Goldapple, K., Segal, Z., Garson, C., Lau, M., Bieling, P., Kennedy, S., & Mayberg, H.S. (2004). Modulation of cortical-limbic pathways in major depression; Treatment-specific effects of cognitive behavioral therapy. Archives of General Psychiatry, 61, 3441.Google Scholar
Hamani, C., Mayberg, H.S., Stone, S., Laxton, A., Haber, S., & Lozano, A.M. (2011). The subcallosal cingulate gyrus in the context of major depression. Biological Psychiatry, 69, 301308.Google Scholar
Holtzheimer, P.E., & Mayberg, H.S. (2011a). Deep brain stimulation for psychiatric disorders. Annual Review of Neuroscience, 34, 289307.Google Scholar
Holtzheimer, P.E., & Mayberg, H.S. (2011b). Stuck in a rut: Rethinking depression and its treatment. Trends in Neuroscience, 34(1), 19. doi: 10.1016/j.tins.2010.10.004 CrossRefGoogle Scholar
Kennedy, S.H., Evans, K.R., Krüger, S., Mayberg, H.S., Meyer, J.H., McCann, S., & Vaccarino, F.J. (2001). Changes in regional brain glucose metabolism measured with positron emission tomography after paroxetine treatment of major depression. The American Journal of Psychiatry, 158(6), 899905.CrossRefGoogle ScholarPubMed
Kennedy, S.H., Konarski, J.Z., Segal, Z.V., Lau, M.A., Bieling, P.J., McIntyre, R.S., & Mayberg, H.S. (2007). Differences in brain glucose metabolism between responders to CBT and venlafaxine in a 16-week randomized controlled trial. The American Journal of Psychiatry, 164(5), 778788.Google Scholar
Konarski, J.Z., Kennedy, S.H., Segal, Z.V., Lau, M., Bieling, P., McIntyre, R.S., & Mayberg, H.S. (2009). Predictors of nonresponse to cognitive behavioural therapy or venlafaxine using glucose metabolism in major depressive disorder. Journal of Psychiatry & Neuroscience, 34(3), 175180.Google ScholarPubMed
Lemogne, C., Delaveau, P., Freton, M., Guionnet, S., & Fossati, P. (2012). Medial prefrontal cortex and the self in major depression. Journal of Affective Disorders, 136(1), e1e11.Google Scholar
Liotti, M., Mayberg, H.S., McGinnis, Brannan, S.L., & Jerabek, P. (2002). Mood challenge in remitted unipolar depression unmaskes disease-specific cerebral blood flow abnormalities. The American Journal of Psychiatry, 159, 18301840.Google Scholar
Lozano, A.M., & Mayberg, H.S. (2015). Treating depression at the source. Scientific American, 312(2), 6873.Google Scholar
Lozano, A.M., Mayberg, H.S., Giacobbe, P., Hamani, C., Craddock, R.C., & Kennedy, S.H. (2008). Subcallosal cingulate gyrus deep brain stimulation for treatment-resistant depression. Biological Psychiatry, 64(6), 461467.Google Scholar
Luu, P., Tucker, D.M., & Makeig, S. (2004). Frontal midline theta and the error-related negativity: Neurophysiological mechanisms of action regulation. Clinical Neurophysiology, 115(8), 18211835.Google Scholar
Mayberg, H.S. (1994). Frontal lobe dysfunction in secondary depression. Journal of Neuropsychiatry and Clinical Neurosciences, 6, 428442.Google Scholar
Mayberg, H.S. (1997). Limbic-cortical dysregulation: A proposed model of depression. Journal of Neuropsychiatry, 9(3), 471481.Google Scholar
Mayberg, H.S. (2003). Modulating dysfunctional limbic-cortical circuits in depression: Towards development of brain-based algorithms for diagnosis and optimised treatment. British Medical Bulletin, 65, 193207.Google Scholar
Mayberg, H.S., Brannan, S.K., Mahurin, R.K., Jerabek, P.A., Brickman, J.S., Tekell, J.L., & Martin, C.C. (1997). Cingulate function in depression: A potential predictor of treatment response. Neuroreport, 8(4), 10571061.Google Scholar
Mayberg, H.S., Brannan, S.K., Tekell, J.L., Silva, J.A., Mahurin, R.K., McGinnis, S., & Jerabek, P.A. (2000). Regional metabolic effects of fluoxetine in major depression: Serial changes and relationship to clinical response. Biological Psychiatry, 48(8), 830843.Google Scholar
Mayberg, H.S., Liotti, M., Brannan, S.K., McGinnis, S., Mahurin, R.K., Jerabek, P.A., & Lancaster, J.L. (1999). Reciprocal limbic-cortical function and negative mood: Converging PET findings in depression and normal sadness. The American Journal of Psychiatry, 156(5), 675682.Google Scholar
Mayberg, H.S., Lozano, A.M., Voon, V., McNeely, H.E., Seminowicz, D., Hamani, C., & Kennedy, S.H. (2005). Deep brain stimulation for treatment-resistant depression. Neuron, 45(5), 651660.Google Scholar
McGrath, C.L., Kelley, M.E., Dunlop, B.W., Holtzheimer, P.E. III, Craighead, W.E., & Mayberg, H.S. (2014). Pretreatment brain states identify likely nonresponse to standard treatments for depression. Biological Psychiatry, 76(7), 527535.Google Scholar
McGrath, C.L., Kelley, M.E., Holtzheimer, P.E., Dunlop, B.W., Craighead, W.E., Franco, A.R., & Mayberg, H.S. (2013). Toward a neuroimaging treatment selection biomarker for major depressive disorder. JAMA Psychiatry, 70(8), 821829.CrossRefGoogle Scholar
Northoff, G., Heinzel, A., De Greck, M., Bermpohl, F., Dobrowolny, H., & Panksepp, J. (2006). Self-referential processing in our brain—A meta-analysis of imaging studies on the self. Neuroimage, 31(1), 440457.Google Scholar
Northoff, G., Wiebking, C., Feinberg, T., & Panksepp, J. (2011). The resting-state hypothesis of major depressive disorder; A translational subcortical-cortical framework for a system disorder. Neuroscience & Biobehavioral Reviews, 35(9), 19291945.Google Scholar
Phillips, M.L., Drevets, W.C., Rauch, S.L., & Lane, R. (2003). Neurobiology of emotion perception II: Implications for major psychiatric disorders. Biological Psychiatry, 54(5), 515528.Google Scholar
Pizzagalli, D.A. (2011). Frontocingulate dysfunction in depression: Toward biomarkers of treatment response. Neuropsychopharmacology, 36(1), 183206.Google Scholar
Poulsen, C., Luu, P., Crane, S.M., Quiring, J., & Tucker, D.M. (2009). Frontolimibic activity and cognitive bias in major depression. Journal of Abnormal Psychology, 118(3), 494506.CrossRefGoogle ScholarPubMed
Ramirez-Mahaluf, J.P., Roxin, A., Mayberg, H.S., & Compte, A. (2017). A computational model of major depression: The role of glutamate dysfunction on cingulo-frontal network dynamics. Cerebral Cortex, 27(1), 660697.Google Scholar
Ressler, K.J., & Mayberg, H.S. (2007). Targeting abnormal neural circuits in mood and anxiety disorders: From the laboratory to the clinic. Nature Neuroscience, 10(9), 11161124.Google Scholar
Riva-Posse, P., Choi, K.S., Holtzheimer, P.E., Crowell, A.L., Garlow, S.J., Rajendra, J.K., & Mayberg, H.S. (2017). A connectomic approach for subcallosal cingulate deep brain stimulation surgery: Prospective targeting in treatment-resistant depression. Molecular Psychiatry, 76, 963969.Google Scholar
Riva-Posse, P., Choi, K.S., Holtzheimer, P.E., McIntyre, C.C., Gross, R.E., Chaturvedi, A., & Mayberg, H.S. (2014). Defining critical white matter pathways mediating successful subcallosal cingulate deep brain stimulation for treatment-resistant depression. Biological Psychiatry, 76, 963969.Google Scholar
Robinson, R.G., Kubos, K.l., Starr, L.B., Rao, K., & Price, T.R. (1984). Mood disorders in stroke patients: Importance of location of lesion. Brain, 107(1), 8193.CrossRefGoogle ScholarPubMed
Savitz, J.B., Rauch, S.L., & Drevets, W.C. (2013). Clinical application of brain imaging for the diagnosis of mood disorders: The current state of play. Molecular Psychiatry, 18(5), 528539.Google Scholar
Saxena, S., Brody, A.L., Ho, M.L., Zohrabi, N., Maidment, K.M., & Baxter, L.R. Jr. (2003). Differential brain metabolic predictors of response to paroxetine in obsessive-compulsive disorder versus major depression. The American Journal of Psychiatry, 160(3), 522532.CrossRefGoogle ScholarPubMed
Seminowicz, D.A., Mayberg, H.S., McIntosh, A.R., Goldapple, K., Kennedy, S., Segal, Z., & Rafi-Tari, S. (2004). Limbic-frontal circuitry in major depression: A path modeling metanalysis. Neuroimage, 22, 409418.Google Scholar
Siegle, G.J., Carter, C.S., & Thase, M.E. (2006). Use of FMRI to predict recovery from unipolar depression with cognitive behavior therapy. The American Journal of Psychiatry, 163(4), 735738.Google Scholar
Siegle, G.J., Thompson, W.K., Collier, A., Berman, S.R., Feldmiller, J., Thase, M.E., & Friedman, E.S. (2012). Toward clinically useful neuroimaging in depression treatment: Prognostic utility of subgenual cingulate activity for determining depression outcome in cognitive therapy across studies, scanners, and patient characteristics. Archives of General Psychiatry, 69(9), 913924.Google Scholar
Snyder, H.R. (2013). Major depressive disorder is associated with broad impairments on neuropsychological measures of executive function: A meta-analysis and review. Psychological Bulletin, 139(1), 81.Google Scholar
Starkstein, S.E., & Robinson, R.G. (1993). Depression in neurologic disease. Baltimore: Johns Hopkins University Press.Google Scholar
Starkstein, S.E., Robinson, R.G., & Price, T.R. (1987). Comparison of cortical and subcortical lesions in the production of poststroke mood disorders. Brain, 110(4), 10451059.Google Scholar
Stuss, D.T., & Benson, D.F. (1986). The frontal lobes. New York: Raven.Google Scholar
Tang, E., & Bassett, D.S. (2017). Control of dynamics in brain networks. arXiv preprint arXiv:1701.01531.Google Scholar
Tenke, C.E., Kayser, J., Pechtel, P., Webb, C.A., Dillon, D.G., Goer, F., & Parsey, R. (2017). Demonstrating test‐retest reliability of electrophysiological measures for healthy adults in a multisite study of biomarkers of antidepressant treatment response. Psychophysiology, 54(1), 3450.Google Scholar
Treadway, M.T., & Leonard, C. (2016). Isolating biomarkers for symptomatic states: Considering symptom–substrate chronometry. Molecular Psychiatry, 21(9), 11801187.Google Scholar
Trivedi, M.H., McGrath, P.J., Fava, M., Parsey, R.V., Kurian, B.T., Phillips, M.L., & Cooper, C. (2016). Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): Rationale and design. Journal of Psychiatric Research, 78, 1123.Google Scholar
Tucker, D.M., & Luu, P. (2007). Neurophysiology of motivated learning: Adaptive mechanisms underlying cognitive bias in depression. Cognitive Therapy Research, 31, 189209.Google Scholar
Tucker, D.M., & Luu, P. (2012). Cognition and neural development. New York, NY: Oxford University Press.Google Scholar
Tucker, D.M., Luu, P., Frishkoff, G., Quiring, J., & Poulsen, C. (2003). Frontolimbic response to negative feedback in depression. Journal of Abnormal Psychology, 112, 667678.Google Scholar
Waters, A.C., & Tucker, D.M. (2013). Positive and negative affect in adolescent self-evaluation: Psychometric information in single trials used to generate dimension-specific ERPs and neural source models. Psychophysiology, 50(6), 538549.Google Scholar
Waters, A.C., & Tucker, D.M. (2016). Principal components of electrocortical activity during self-evaluation indicate depressive symptom severity. Social Cognitive and Affective Neuroscience, 11(8), 13351343.Google Scholar
Williams, L.M. (2016). Defining biotypes for depression and anxiety based on large‐scale circuit dysfunction: A theoretical review of the evidence and future directions for clinical translation. Depression and Anxiety, 34(1), 924.CrossRefGoogle ScholarPubMed
Yoshimura, S., Okamoto, Y., Matsunaga, M., Onoda, K., Okada, G., Kunisato, Y., & Yamawaki, S. (2017). Cognitive behavioral therapy changes functional connectivity between medial prefrontal and anterior cingulate cortices. Journal of Affective Disorders, 208, 610614.Google Scholar