Abstract
Over the past decade, various N-methyl-d-aspartate modulators have failed in clinical trials, underscoring the challenges of developing novel rapid-acting antidepressants based solely on the receptor or regional targets of ketamine. Thus, identifying the effect of ketamine on the brain circuitry and networks is becoming increasingly critical. In this longitudinal functional magnetic resonance imaging study of data from 265 participants, we used a validated predictive model approach that allows the full assessment of brain functional connectivity, without the need for seed selection or connectivity summaries. First, we identified a connectome fingerprint (CFP) in healthy participants (Cohort A, n = 25) during intravenous infusion of a subanesthetic dose of ketamine, compared to normal saline. We then demonstrated the robustness and reproducibility of the discovered ketamine CFP in two separate healthy samples (Cohort B, n = 22; Cohort C, n = 18). Finally, we investigated the ketamine CFP connectivity at 1-week post treatment in major depressive disorder patients randomized to 8 weeks of sertraline or placebo (Cohort D, n = 200). We found a significant, robust, and reproducible ketamine CFP, consistent with reduced connectivity within the primary cortices and within the executive network, but increased connectivity between the executive network and the rest of the brain. Compared to placebo, the ketamine CFP connectivity changes at 1 week predicted response to sertraline at 8 weeks. In each of Cohorts A–C, ketamine significantly increased connectivity in a previously identified antidepressant CFP. Investigating the brain connectivity networks, we successfully identified a robust and reproducible ketamine biomarker that is related to the mechanisms of antidepressants.
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References
Berman RM, Cappiello A, Anand A, Oren DA, Heninger GR, Charney DS, et al. Antidepressant effects of ketamine in depressed patients. Biol Psychiatry. 2000;47:351–4.
Murrough JW, Iosifescu DV, Chang LC, Al Jurdi RK, Green CE, Perez AM, et al. Antidepressant efficacy of ketamine in treatment-resistant major depression: a two-site randomized controlled trial. Am J Psychiatry. 2013;170:1134–42.
Zarate CA Jr., Singh JB, Carlson PJ, Brutsche NE, Ameli R, Luckenbaugh DA, et al. A randomized trial of an N-methyl-D-aspartate antagonist in treatment-resistant major depression. Arch Gen Psychiatry. 2006;63:856–64.
Kraus C, Wasserman D, Henter ID, Acevedo-Diaz E, Kadriu B, Zarate CA, Jr. The influence of ketamine on drug discovery in depression. Drug Discov Today. 2019. https://doi.org/10.1016/j.drudis.2019.07.007.
Krystal JH, Sanacora G, Duman RS. Rapid-acting glutamatergic antidepressants: the path to ketamine and beyond. Biol Psychiatry. 2013;73:1133–41.
Finn ES, Shen X, Scheinost D, Rosenberg MD, Huang J, Chun MM, et al. Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity. Nat Neurosci. 2015;18:1664–71.
Nemati S, Abdallah CG. Increased cortical thickness in patients with major depressive disorder following antidepressant treatment. Chronic Stress. 2020;4:247054701989996.
Akiki TJ, Averill CL, Wrocklage KM, Scott JC, Averill LA, Schweinsburg B, et al. Default mode network abnormalities in posttraumatic stress disorder: a novel network-restricted topology approach. NeuroImage 2018;176:489–98.
Shen X, Finn ES, Scheinost D, Rosenberg MD, Chun MM, Papademetris X, et al. Using connectome-based predictive modeling to predict individual behavior from brain connectivity. Nat Protoc. 2017;12:506–18.
Akiki TJ, Abdallah CG. Determining the hierarchical architecture of the human brain using subject-level clustering of functional networks. Sci Rep. 2019;9:19290.
Nemati S, Akiki TJ, Roscoe J, Ju Y, Averill CL, Fouda S, et al. A unique brain connectome fingerprint predates and predicts response to antidepressants. iScience. 2020;23:100800.
Abi-Dargham A, Horga G. The search for imaging biomarkers in psychiatric disorders. Nat Med. 2016;22:1248–55.
Abdallah CG, Averill CL, Salas R, Averill LA, Baldwin PR, Krystal JH, et al. Prefrontal connectivity and glutamate transmission: relevance to depression pathophysiology and ketamine treatment. Biol Psychiatry Cogn Neurosci Neuroimaging. 2017;2:566–74.
D’Souza DC, Carson RE, Driesen N, Johannesen J, Ranganathan M, Krystal JH, et al. Dose-related target occupancy and effects on circuitry, behavior, and neuroplasticity of the glycine transporter-1 inhibitor PF-03463275 in healthy and schizophrenia subjects. Biol Psychiatry. 2018;84:413–21.
Driesen NR, McCarthy G, Bhagwagar Z, Bloch MH, Calhoun VD, D’Souza DC, et al. The impact of NMDA receptor blockade on human working memory-related prefrontal function and connectivity. Neuropsychopharmacology. 2013;38:2613–22.
Trivedi MH, McGrath PJ, Fava M, Parsey RV, Kurian BT, Phillips ML, et al. Establishing moderators and biosignatures of antidepressant response in clinical care (EMBARC): rationale and design. J Psychiatr Res. 2016;78:11–23.
Javitt DC, Carter CS, Krystal JH, Kantrowitz JT, Girgis RR, Kegeles LS, et al. Utility of imaging-based biomarkers for glutamate-targeted drug development in psychotic disorders: a randomized clinical trial. JAMA Psychiatry. 2018;75:11–9.
Greenberg T, Chase HW, Almeida JR, Stiffler R, Zevallos CR, Aslam HA, et al. Moderation of the relationship between reward expectancy and prediction error-related ventral striatal reactivity by anhedonia in unmedicated major depressive disorder: findings from the EMBARC study. Am J Psychiatry. 2015;172:881–91.
Glasser MF, Sotiropoulos SN, Wilson JA, Coalson TS, Fischl B, Andersson JL, et al. The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage. 2013;80:105–24.
Abdallah CG, Averill CL, Ramage AE, Averill LA, Alkin E, Nemati S, et al. Reduced salience and enhanced central executive connectivity following PTSD treatment. Chronic Stress. 2019;3:2470547019838971.
Abdallah CG, Averill CL, Ramage AE, Averill LA, Goktas S, Nemati S, et al. Salience network disruption in U.S. Army Soldiers with posttraumatic stress disorder. Chronic Stress. 2019;3:2470547019850467.
Abdallah CG, Dutta A, Averill CL, McKie S, Akiki TJ, Averill LA, et al. Ketamine, but Not the NMDAR antagonist lanicemine, increases prefrontal global connectivity in depressed patients. Chronic Stress. 2018;2:2470547018796102.
Salimi-Khorshidi G, Douaud G, Beckmann CF, Glasser MF, Griffanti L, Smith SM. Automatic denoising of functional MRI data: combining independent component analysis and hierarchical fusion of classifiers. NeuroImage. 2014;90:449–68.
Griffanti L, Salimi-Khorshidi G, Beckmann CF, Auerbach EJ, Douaud G, Sexton CE, et al. ICA-based artefact removal and accelerated fMRI acquisition for improved resting state network imaging. NeuroImage. 2014;95:232–47.
Burgess GC, Kandala S, Nolan D, Laumann TO, Power JD, Adeyemo B, et al. Evaluation of denoising strategies to address motion-correlated artifacts in resting-state functional magnetic resonance imaging data from the Human Connectome Project. Brain Connect. 2016;6:669–80.
Diedrichsen J, Balsters JH, Flavell J, Cussans E, Ramnani N. A probabilistic MR atlas of the human cerebellum. NeuroImage. 2009;46:39–46.
Fan L, Li H, Zhuo J, Zhang Y, Wang J, Chen L, et al. The human brainnetome atlas: a new brain atlas based on connectional architecture. Cereb Cortex. 2016;26:3508–26.
Glasser MF, Coalson TS, Robinson EC, Hacker CD, Harwell J, Yacoub E, et al. A multi-modal parcellation of human cerebral cortex. Nature. 2016;536:171–8.
Duman RS, Aghajanian GK. Synaptic dysfunction in depression: potential therapeutic targets. Science. 2012;338:68–72.
Abdallah CG, Sanacora G, Duman RS, Krystal JH. The neurobiology of depression, ketamine and rapid-acting antidepressants: Is it glutamate inhibition or activation? Pharm Ther. 2018;190:148–58.
Abdallah CG, Averill LA, Collins KA, Geha P, Schwartz J, Averill C, et al. Ketamine treatment and global brain connectivity in major depression. Neuropsychopharmacology. 2017;42:1210–9.
Holmes SE, Scheinost D, Finnema SJ, Naganawa M, Davis MT, DellaGioia N, et al. Lower synaptic density is associated with depression severity and network alterations. Nat Commun. 2019;10:1529.
Kraus C, Mkrtchian A, Kadriu B, Nugent AC, Zarate CA, Jr., Evans JW. Evaluating global brain connectivity as an imaging marker for depression: influence of preprocessing strategies and placebo-controlled ketamine treatment. Neuropsychopharmacology. 2020. https://doi.org/10.1038/s41386-020-0624-0.
Murrough JW, Abdallah CG, Anticevic A, Collins KA, Geha P, Averill LA, et al. Reduced global functional connectivity of the medial prefrontal cortex in major depressive disorder. Hum Brain Mapp. 2016;37:3214–23.
Scheinost D, Holmes SE, DellaGioia N, Schleifer C, Matuskey D, Abdallah CG, et al. Multimodal investigation of network level effects using intrinsic functional connectivity, anatomical covariance, and structure-to-function correlations in unmedicated major depressive disorder. Neuropsychopharmacology. 2018;43:1119–27.
Wang L, Dai Z, Peng H, Tan L, Ding Y, He Z, et al. Overlapping and segregated resting-state functional connectivity in patients with major depressive disorder with and without childhood neglect. Hum Brain Mapp. 2014;35:1154–66.
Kaiser RH, Andrews-Hanna JR, Wager TD, Pizzagalli DA. Large-scale network dysfunction in major depressive disorder: a meta-analysis of resting-state functional connectivity. JAMA Psychiatry. 2015;72:603–11.
Sheline YI, Price JL, Yan Z, Mintun MA. Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus. Proc Natl Acad Sci USA. 2010;107:11020–5.
Yu M, Linn KA, Shinohara RT, Oathes DJ, Cook PA, Duprat R, et al. Childhood trauma history is linked to abnormal brain connectivity in major depression. Proc Natl Acad Sci USA. 2019;116:8582–90.
Chin Fatt CR, Jha MK, Cooper CM, Fonzo G, South C, Grannemann B, et al. Effect of intrinsic patterns of functional brain connectivity in moderating antidepressant treatment response in major depression. Am J Psychiatry. 2020;177:143–54.
Driesen NR, McCarthy G, Bhagwagar Z, Bloch M, Calhoun V, D’Souza DC, et al. Relationship of resting brain hyperconnectivity and schizophrenia-like symptoms produced by the NMDA receptor antagonist ketamine in humans. Mol Psychiatry. 2013;18:1199–204.
Anticevic A, Corlett PR, Cole MW, Savic A, Gancsos M, Tang Y, et al. N-methyl-D-aspartate receptor antagonist effects on prefrontal cortical connectivity better model early than chronic schizophrenia. Biol Psychiatry. 2015;77:569–80.
Anticevic A, Gancsos M, Murray JD, Repovs G, Driesen NR, Ennis DJ, et al. NMDA receptor function in large-scale anticorrelated neural systems with implications for cognition and schizophrenia. Proc Natl Acad Sci USA. 2012;109:16720–5.
Bonhomme V, Vanhaudenhuyse A, Demertzi A, Bruno MA, Jaquet O, Bahri MA, et al. Resting-state network-specific breakdown of functional connectivity during ketamine alteration of consciousness in volunteers. Anesthesiology. 2016;125:873–88.
Mueller F, Musso F, London M, de Boer P, Zacharias N, Winterer G. Pharmacological fMRI: effects of subanesthetic ketamine on resting-state functional connectivity in the default mode network, salience network, dorsal attention network and executive control network. NeuroImage Clin. 2018;19:745–57.
Friston KJ, Buechel C, Fink GR, Morris J, Rolls E, Dolan RJ. Psychophysiological and modulatory interactions in neuroimaging. NeuroImage. 1997;6:218–29.
Abdallah CG, Sanacora G, Duman RS, Krystal JH. Ketamine and rapid-acting antidepressants: a window into a new neurobiology for mood disorder therapeutics. Annu Rev Med. 2015;66:509–23.
McEwen BS. Neurobiological and systemic effects of chronic stress. Chronic Stress. 2017;1:1–11.
Abdallah CG, Averill LA, Akiki TJ, Raza M, Averill CL, Gomaa H, et al. The neurobiology and pharmacotherapy of posttraumatic stress disorder. Annu Rev Pharm Toxicol. 2019;59:171–89.
Abdallah CG, Jackowski A, Salas R, Gupta S, Sato JR, Mao X, et al. The nucleus accumbens and ketamine treatment in major depressive disorder. Neuropsychopharmacology. 2017;42:1739–46.
Melo A, Kokras N, Dalla C, Ferreira C, Ventura-Silva AP, Sousa N, et al. The positive effect on ketamine as a priming adjuvant in antidepressant treatment. Transl Psychiatry. 2015;5:e573.
Hare B, Ghosal S, Duman R. Rapid acting antidepressants in chronic stress models: molecular and cellular mechanisms. Chronic Stress. 2017;1:1–16.
Abdallah CG, De Feyter HM, Averill LA, Jiang L, Averill CL, Chowdhury GMI, et al. The effects of ketamine on prefrontal glutamate neurotransmission in healthy and depressed subjects. Neuropsychopharmacology. 2018. https://doi.org/10.1038/s41386-018-0136-3.
Murrough JW, Abdallah CG, Mathew SJ. Targeting glutamate signalling in depression: progress and prospects. Nat Rev Drug Discov. 2017;16:472–86.
Liu RJ, Duman C, Kato T, Hare B, Lopresto D, Bang E, et al. GLYX-13 produces rapid antidepressant responses with key synaptic and behavioral effects distinct from ketamine. Neuropsychopharmacology. 2017;42:1231–42.
Li N, Lee B, Liu RJ, Banasr M, Dwyer JM, Iwata M, et al. mTOR-dependent synapse formation underlies the rapid antidepressant effects of NMDA antagonists. Science. 2010;329:959–64.
Abdallah CG, Averill LA, Gueorguieva R, Goktas S, Purohit P, Ranganathan M, et al. Modulation of the antidepressant effects of ketamine by the mTORC1 inhibitor rapamycin. Neuropsychopharmacology. 2020;45:990–7.
Autry AE, Adachi M, Nosyreva E, Na ES, Los MF, Cheng PF. et al. NMDA receptor blockade at rest triggers rapid behavioural antidepressant responses. Nature. 2011;475:91–5. https://doi.org/10.1038/nature10130.
Acknowledgements
The authors would like to thank the subjects who participated in these studies for their invaluable contribution. Data used in the preparation of this paper were obtained and analyzed from the controlled access data sets distributed from the NIMH-supported National Database for Clinical Trials (NDCT). NDCT is a collaborative informatics system created by the National Institute of Mental Health to provide a national resource to support and accelerate discovery related to clinical trial research in mental health. Data set identifier(s): STU 092010-151; Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC). This paper reflects the views of the authors and may not reflect the opinions or views of the NIMH or of the individuals submitting original data to the NDCT.
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Conceptualization: CGA, JHK, and NRD; methodology: CGA; data curation: KHA, SN, MR, PTM, DCD, DHM, and NRD; formal analysis: CGA; investigation: CGA, KHA, LAA, SN, CLA, SF, MR, PTM, DCD, DHM, JHK, and NRD; writing—original draft: CGA, JHK, and NRD; writing—review/edit: all authors; funding acquisition: CGA, DHM, JHK, and NRD; resources: CGA, LAA, and NRD; supervision: CGA, JHK, and NRD.
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Abdallah, C.G., Ahn, KH., Averill, L.A. et al. A robust and reproducible connectome fingerprint of ketamine is highly associated with the connectomic signature of antidepressants. Neuropsychopharmacol. 46, 478–485 (2021). https://doi.org/10.1038/s41386-020-00864-9
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DOI: https://doi.org/10.1038/s41386-020-00864-9
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