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News Brief—Dead End for Lilly mGluR Schizophrenia Drug

29 August 2012. Eli Lilly and Company announced in a press release today that they will stop Phase 3 clinical trials of a schizophrenia drug targeting the metabotropic glutamate receptor. This was not unexpected, as just last month Lilly had revealed further disappointing trial results of the mGluR2/3 agonist pomaglumetad methionil (also called LY2140023). At the time, researchers interviewed by SRF had mixed opinions about the way forward (see SRF news story), and a Lilly spokesperson had told SRF that they were still pressing forward with the development of LY2140023, including analyzing data on mGluR2/3 agonists as adjunctive therapy to approved schizophrenia drugs. In the latest press release, they write that this Phase 2 study also failed to meet its primary endpoint.—Hakon Heimer.

Comments on Related News


Related News: Opinions Mixed on Future for Lilly’s mGluR2/3 Agonist for Schizophrenia

Comment by:  Philip Seeman (Disclosure)
Submitted 15 August 2012
Posted 22 August 2012

The Lilly results of 11 July 2012 are not surprising, considering that the main ingredient of LY2140023 is LY404039, which is both a glutamate agonist and a weak partial dopamine agonist with only one-hundredth the potency of aripiprazole (Seeman and Guan, 2009; Seeman, 2012a), and considering that closer inspection of the clinical data (Kinon et al., 2011) showed that olanzapine was effective in schizophrenia, while LY2140023 was not (Seeman, 2012b).

References:

Kinon BJ, Zhang L, Millen BA, Osuntokun OO, Williams JE, Kollack-Walker S, Jackson K, Kryzhanovskaya L, Jarkova N, . A multicenter, inpatient, phase 2, double-blind, placebo-controlled dose-ranging study of LY2140023 monohydrate in patients with DSM-IV schizophrenia. J Clin Psychopharmacol . 2011 Jun ; 31(3):349-55. Abstract

Seeman P, Guan HC. Glutamate agonist LY404,039 for treating schizophrenia has affinity for the dopamine D2(High) receptor. Synapse. 2009 Oct ; 63(10):935-9. Abstract

Seeman P. An agonist at glutamate and dopamine D2 receptors, LY404039. Neuropharmacology. 2012a Jul 4. Abstract

Seeman P. Comment on "A multicenter, inpatient, phase 2, double-blind, placebo-controlled dose-ranging study of LY2140023 monohydrate in patients with DSM-IV schizophrenia" by Kinon et al. J Clin Psychopharmacol. 2012b Apr ; 32(2):291-2; author reply 292-293. Abstract

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Related News: Opinions Mixed on Future for Lilly’s mGluR2/3 Agonist for Schizophrenia

Comment by:  Hugo Geerts
Submitted 15 August 2012
Posted 22 August 2012

This is indeed another setback for the schizophrenia patient community, and it underscores the difficulty of translating animal model outcomes to the clinical situation. We have to think about introducing a new technology in schizophrenia drug discovery and development that would combine the best of preclinical animal information, but transplanted into a humanized environment to reverse this string of clinical failures.

One such approach is Quantitative Systems or Network Pharmacology, a computer-based mechanistic disease model of biophysically realistic neuronal networks that combines preclinical neurophysiology with human pathology, and clinical and imaging data (the topic of a recent NIH White Paper). Such an approach can be calibrated with retrospective clinical data, and then used to predict and examine future clinical trials. Applying this quantitative paradigm to the (also much publicized) failure of Dimebon in AD, researchers found that there was a fundamental off-target effect that precluded Dimebon from having cognitive benefits. Further analyses suggested that an imbalance in a common dopaminergic phenotype could increase part of the clinical signal difference as observed in the first (successful) Phase 2 trial.

In the case of schizophrenia, we find that affecting glutamatergic (such as with the mGluR2/R3 agonist) or GABA neurotransmission almost always leads to an inverse U-shaped dose response, because of the intrinsic balance between excitation and inhibition in cortical networks. Using such an approach forces discovery scientists to look beyond the single target and think about the impact on networks and circuits that ultimately drive human behavior and pathology in CNS disorders.

Unlike the traditional, currently used "cartoon"-based qualitative drawings, this approach allows for a quantitative outcome that, in principle, can help define the optimal "sweet spot" of the dose response by looking at the outcome of endophenotypes such as BOLD fMRI.

References:

Athan Spiros, Hugo Geerts. 2012. A quantitative way to estimate clinical off-target effects for human membrane brain targets in CNS Research and Development. Exp Pharmacology, 4; 53-61.

Athan Spiros, Patrick Roberts, Hugo Geerts. (2012) A Quantitative Systems Pharmacology Computer Model for Schizophrenia Efficacy and Extrapyramidal Side Effects, Drug Dev. Res, 73(4): 1098-1109.

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Related News: SIRS 2014—Refining Schizophrenia Clinical Drug Trials

Comment by:  Anthony Grace, SRF Advisor (Disclosure)
Submitted 4 June 2014
Posted 4 June 2014

This was an important symposium, but I am concerned about the impression that these findings suggest a problem with translating data from animal models to the clinic. In order to translate effectively, one must use an animal model that recapitulates as much of the disease state as possible, and acute pharmacological challenges are inadequate for this. Developmental models should be a more effective screen. But perhaps more important, there is a very big difference between animal models and clinical trials: In animal models, the first therapeutic drug that the animal sees is the novel target compound. In contrast, clinical trials comprise patients that have been treated for antipsychotic drugs for decades, then withdrawn for only a single week before the test compound is evaluated.

It has been known for quite some time that repeated D2 antagonists change the brain in substantial ways. In our recent paper (Gill et al., 2014), we found that a GABAA alpha 5 compound that was highly effective in reversing dopamine neuron hyper-responsivity and amphetamine hyperlocomotion in MAM model rats was completely ineffective if the MAM rats were given just three weeks of haloperidol and withdrawn from the drug for one week. Therefore, once maintained on a D2 antipsychotic drug, we posit that the system changes from a hippocampal overdriven dopamine system to a postsynaptic dopamine receptor supersensitivity psychosis, such that only another D2 antagonist can now effectively replace the drug that had been withdrawn. We need to rethink clinical trial design if we are to effectively evaluate drugs with novel targets, or we may never get away from D2 antagonist therapy.

References:

Gill KM, Cook JM, Poe MM, Grace AA. Prior antipsychotic drug treatment prevents response to novel antipsychotic agent in the methylazoxymethanol acetate model of schizophrenia. Schizophr Bull. 2014 Mar ;40(2):341-50. Abstract

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Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia

Comment by:  Hugo Geerts
Submitted 26 August 2014
Posted 26 August 2014

This is a very interesting contribution to improve the understanding of the progressive nature of schizophrenia pathology. Ketamine-induced effects have been used for a long time in healthy volunteers or in animal models, both rodents and non-human primates to "mimic" schizophrenia pathology. The observation that ketamine mimics more the very early schizophrenia or the at-risk state but not the more chronic pathology helps to explain the dissociation between effects of compounds in ketamine-induced deficits and in chronic schizophrenia, for example, nicotine (D'Souza et al., 2012), glycine transport inhibitor (D'Souza et al., 2012), haloperidol (Oranje et al., 2009), and lamotrigine (Goff et al., 2007).

The impact of these findings, if reproduced in a longitudinal study, is very important. This model of ketamine-induced deficit can be used in animals to test new experimental interventions in very early psychosis or in at-risk subjects. This is a patient group that is currently underserved in terms of therapeutic interventions and for which there is great interest. For the first time, we now have a model that mimics important aspects of the early schizophrenia pathology, and the hope is that when addressing these changes with the right medication early on, one could postpone or delay the onset of overt schizophrenia pathology, which could be the beginning of a preventive strategy.

References:

D'Souza DC, Ahn K, Bhakta S, Elander J, Singh N, Nadim H, Jatlow P, Suckow RF, Pittman B, Ranganathan M. Nicotine fails to attenuate ketamine-induced cognitive deficits and negative and positive symptoms in humans: implications for schizophrenia. Biol Psychiatry . 2012 Nov 1 ; 72(9):785-94. Abstract

D'Souza DC, Singh N, Elander J, Carbuto M, Pittman B, Udo De Haes J, Sjogren M, Peeters P, Ranganathan M, Schipper J. Glycine transporter inhibitor attenuates the psychotomimetic effects of ketamine in healthy males: preliminary evidence. Neuropsychopharmacology . 2012 Mar ; 37(4):1036-46. Abstract

Oranje B, Gispen-de Wied CC, Westenberg HG, Kemner C, Verbaten MN, Kahn RS. Haloperidol counteracts the ketamine-induced disruption of processing negativity, but not that of the P300 amplitude. Int J Neuropsychopharmacol . 2009 Jul ; 12(6):823-32. Abstract

Goff DC, Keefe R, Citrome L, Davy K, Krystal JH, Large C, Thompson TR, Volavka J, Webster EL. Lamotrigine as add-on therapy in schizophrenia: results of 2 placebo-controlled trials. J Clin Psychopharmacol . 2007 Dec ; 27(6):582-9. Abstract

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Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia

Comment by:  Alexandre Seillier
Submitted 9 September 2014
Posted 11 September 2014

The "Ketamine Model" Revived?
Despite the seminal review by Jentsch and Roth arguing that long-term, rather than acute administration of NMDA antagonists, such as phencyclidine (PCP) and ketamine, may more isomorphically model schizophrenia (Jentsch and Roth, 1999), acute ketamine remained one of the most widely utilized pharmacological models in both humans and rodents. Recently, Dawson and co-workers added to the accumulating body of evidence that "alterations in brain circuitry that result from chronic, but not from acute, NMDA receptor blockade most accurately reflect the systems level differences in brain network functioning seen in schizophrenia" (Dawson et al., 2014a; Dawson et al., 2014b). Indeed, using brain network connectivity, they reported that, "at a systems level, the mechanisms through which acute ketamine treatment induces schizophrenia-like symptoms may be profoundly divergent from those that contribute to these symptoms in the disorder."

This new study by Anticevic et al. (2014) might have resolved the paradox of acute ketamine-induced hyperfrontality given the hypofrontality observed in schizophrenia. As previously shown in both healthy humans and mice (Dawson et al., 2014a; Driesen et al., 2013), acute ketamine administration was associated with increased prefrontal cortex connectivity. On the other hand, whereas chronic schizophrenics had reduced prefrontal cortex functional connectivity, patients in the early stage of schizophrenia showed increased prefrontal cortex functional connectivity. As stated by the authors, "these data point to a qualitative difference between NMDAR antagonist and chronic schizophrenia effects, suggesting that ketamine's effect on prefrontal cortex connectivity may be more relevant to particular illness stages."

Longitudinal studies will be necessary to confirm that the "phase of illness is an important moderator of the prefrontal cortex functional connectivity in schizophrenia." The authors also addressed some discrepancies that need to be highlighted. First, the reduced and the increased prefrontal cortex functional connectivity in chronic versus early-stage schizophrenia, respectively, were observed in distinct prefrontal areas, namely the right middle frontal gyrus and the left superior frontal gyrus, respectively. Second, the cross-validation of the pharmacological and clinical analysis failed to reach significance; i.e., acute ketamine did not significantly change connectivity in the regions identified in the clinical study. Although it has limitations, this study should inform the application of acute ketamine as a translational model that may better approximate some early stage of schizophrenia.

References:

Dawson N, McDonald M, Higham DJ, Morris BJ, Pratt JA (2014a) Subanesthetic Ketamine Treatment Promotes Abnormal Interactions between Neural Subsystems and Alters the Properties of Functional Brain Networks. Neuropsychopharmacology 39:1786-98. Abstract

Dawson N, Xiao X, McDonald M, Higham DJ, Morris BJ, Pratt JA (2014b) Sustained NMDA receptor hypofunction induces compromised neural systems integration and schizophrenia-like alterations in functional brain networks. Cereb Cortex 24: 452-464. Abstract

Driesen NR, McCarthy G, Bhagwagar Z, Bloch M, Calhoun V, D'Souza DC et al (2013) Relationship of resting brain hyperconnectivity and schizophrenia-like symptoms produced by the NMDA receptor antagonist ketamine. Mol Psychiatry 18:1199-1204. Abstract

Jentsch JD, Roth RH (1999) The neuropsychopharmacology of phencyclidine: from NMDA receptor hypofunction to the dopamine hypothesis of schizophrenia. Neuropsychopharmacology 20: 201-225. Abstract

View all comments by Alexandre Seillier

Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia

Comment by:  Albert Adell
Submitted 10 September 2014
Posted 16 September 2014

The paper by Anticevic and co-workers, as well as the commentary by Hugo Geerts, points to a very interesting issue on the similitude of the ketamine model with schizophrenia. In a previous mini-review, we anticipated that it would be conceivable that acute administration of NMDA receptor antagonists would lead to a reversible malfunctioning of PV-containing interneurons, whereas in schizophrenia, a damage of these neurons may take place at early stages of neurodevelopment (Adell et al., 2012). In summary, acute NMDA antagonism would resemble the early stage of schizophrenia, whereas chronic exposure better models the more chronic pathology of the illness.

References:

Adell A, Jiminez-Sanchez L, Lopez-Gil X, Roman T. Is the Acute NMDA Receptor Hypofunction a Valid Model of Schizophrenia? Schizophr Bull 38(1): 9-14. Abstract

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Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia

Comment by:  Didier Pinault
Submitted 25 September 2014
Posted 26 September 2014

Acute Ketamine Dramatically Amplifies Network Gamma (30-80 Hz) and Higher-Frequency Oscillations
N-methyl D-aspartate receptors play a key role in synaptic plasticity, memory processes, and in the modulation of field oscillations. The non-competitive NMDAR antagonist ketamine has context-dependent and dose-dependent multiple properties, including positive and negative effects. For instance, a single sub-anesthetic administration can disturb cognitive and perceptual processes and induce schizophreniform psychosis in healthy subjects (Krystal et al., 1994; Adler et al., 1998; Newcomer et al., 1999; Hetem et al., 2000); puzzlingly, but of importance, ketamine can generate a durable antidepressant effect in patients refractory to conventional antidepressant therapies (Zarate et al., 2006; Fond et al., 2014; McGirr et al., 2014).

More specifically, Anticevic and colleagues (2014), using brain scans, recently revealed that a single sub-anesthetic administration of ketamine in healthy subjects at rest produces in the prefrontal cortex a state of hyperconnectivity, which resembles that recorded in people in the early stages of schizophrenia but not in patients with chronic (several years' duration) schizophrenia. Also, using fMRI in healthy human subjects, Driesen and colleagues (Driesen et al., 2013) demonstrated that the NMDA receptor antagonist ketamine increases global brain functional connectivity and reduces negative symptoms, suggesting that the ketamine-induced increase in connectivity corresponds to a state of enhanced cortical function. The acute ketamine effects appear quickly (~1-2 minutes) and are transient. In the following, we will see that these fresh clinical findings are consistent with preclinical studies demonstrating that, in rodents, non-competitive NMDAR antagonists increase the amount of field (or network) gamma frequency oscillations (GFOs; 30-80 Hz) in cortical and subcortical regions. In healthy human subjects, ketamine increases the power of GFOs and decreases that of delta oscillations during auditory-evoked network oscillations (Hong et al., 2010).

What does "hyperconnectivity" mean? From clinical imaging studies, functional connectivity is assessed by the degree of correlation between pairwise functional connections from multiple functional cortical and subcortical regions. What does it mean in terms of neural excitatory and inhibitory activities, network oscillations, and cellular firing?

In rodents a single sub-anesthetic administration of ketamine quickly and transiently induces abnormal behavior (hyperlocomotion, ataxia), memory deficits, and abnormally persistent and generalized hypersynchronized (200-400 percent increased power) ongoing GFOs (Ma and Leung, 2007; Chrobak et al., 2008; Pinault, 2008; Hakami et al., 2009; Ehrlichman et al., 2009; Kocsis, 2012). The gamma frequency at maximal power is significantly increased by approximately 10 Hz on average (Pinault, 2008). The amount of ongoing higher-frequency (>80 Hz) oscillations is also increased following a single sub-anesthetic administration (<10 mg/kg) of ketamine (Hakami et al., 2009; Hunt et al., 2006; Kulikova et al., 2012).

In addition, NMDAR antagonists transiently disrupt the expression, not the induction, of long-term potentiation in the thalamocortical system (Kulikova et al., 2012), disorganize action potential firing in rat prefrontal cortex (Molina et al., 2014), increase the firing in fast-spiking neurons, and decrease that in regularly spiking neurons (Homayoun and Moghaddam, 2007). These results suggest that the amount of ongoing GFOs is inversely related to synaptic potentiation in the thalamocortical system (Kulikova et al., 2012). They also suggest that the ketamine-induced state results in part from dysfunction of cortical GABAergic interneurons that would lead to hyperexcitation of projection glutamatergic neurons and to glutamate release (Homayoun and Moghaddam, 2007).

Following the subcutaneous administration of a low dose (<10 mg/kg) of ketamine, both the duration and the amplitude of spontaneously occurring GFOs significantly increase in the rat frontal, parietal, and occipital cortices (Pinault, 2008; Hakami et al., 2009). From a mathematical viewpoint (Cadonic and Albensi, 2014), it was proposed that natural, physiological ongoing GFOs operate like damped harmonic oscillators, which would leave room for synaptic potentiation, learning, and memory, whereas ketamine-induced persistently amplified GFOs run like forced harmonic oscillators, which would disrupt the network ability in information processing and reduce the expression of synaptic potentiation (Pinault, 2014). This might be a key neurophysiological substrate of the functional hyperconnectivity observed by Anticevic and colleagues (2014) and by Driesen and colleagues (Driesen et al., 2013).

There is a growing body of evidence suggesting that the NMDAR antagonist ketamine modulates not only GFOs and higher-frequency oscillations, as mentioned above, but also lower-frequency oscillations, including alpha, theta, and delta oscillations (Ehrlichman et al., 2009; Hong et al., 2010; Palenicek et al., 2011; Tsuda et al., 2007). This broad-spectrum effect depends on the injected dose, the experimental and recording conditions, and on the anatomo-functional properties of the structures under investigation. For instance, under in vivo conditions, a single low-dose (<10 mg/kg) ketamine administration alters specifically GFOs and higher-frequency oscillations (Pinault, 2008; Hakami et al., 2009; Ma and Leung, 2007), while higher doses in addition affect slower rhythms (Ehrlichman et al., 2009; Hunt et al., 2006; Palenicek et al., 2011; Caixeta et al., 2013; Hiyoshi et al., 2014; Nicolas et al., 2011; Buzsaki, 1991). Therefore, we must be prudent when comparing results and inferring mechanisms from studies using different doses of NMDAR antagonists and various and diverse animal and network models. This is fundamental for basic-clinical translational understanding.

Investigating the pathophysiology of schizophrenia in relation to "noise and signal-to-noise ratio" is an appealing basic-clinical translational way to understand the neural mechanisms underlying the multiple symptoms that characterize this complex and heterogeneous neurobiological disease (Rolls et al., 2008). I recently argued on the notion of network signal-to-noise ratio (Pinault, 2014). In any system, both the amount of the ongoing (background or baseline) activity and the amplitude (or power) of its global response to the activation of its inputs are indicators of its state and functionality. The possible noise-signal interplay(s) might in part explain some disparities between findings (e.g., increases and decreases in GFOs in patients with schizophrenia; see SRF Live Discussion organized by Peter Uhlhaas and Kevin Spencer).

More precisely, in the rat thalamocortical system, ketamine simultaneously increases the power of spontaneously occurring GFOs (signature of a change in the state of the system) and decreases sensory-evoked GFOs (signature of a disturbance of the functionality of the system) (Pinault, 2008; Hakami et al., 2009; Kulikova et al., 2012). Assuming that sensory-evoked GFOs include a "true" sensory-related component, the ketamine-induced gamma noise amplification decreases the ability of the thalamocortical system to discriminate the sensory-evoked gamma signal drowned in the noise. In other words, the NMDAR antagonist ketamine decreases the gamma signal-to-noise ratio during sensory information processing. Such a ratio may be considered as a suitable neurophysiological marker of neural networks to evaluate their function and dysfunction.

This dramatically excessive ongoing gamma noise, which might be involved in the ketamine-induced state of hyperconnectivity in healthy subjects (Anticevic et al., 2014; Driesen et al., 2013), is thought to affect global brain state and operation, and to contribute to psychosis. Moreover, continuous and stereotyped GFOs might be responsible for clinical positive symptoms (Llinas et al., 1999). Furthermore, ongoing abnormally hypersynchronized GFOs have been recorded in patients experiencing sensory hallucinations (Baldeweg et al., 1998; Behrendt, 2003; Spencer et al., 2004; Ffytche, 2008; Becker et al., 2009). Hypersynchronized GFOs in cortico-thalamo-cortical systems are thought to play a key role during the appearance of hallucinations (Baldeweg et al., 1998; Behrendt, 2003), raising the question as to whether persistent amplification of ongoing GFOs could somehow conceal function-related GFOs in the corresponding brain networks.

References

Adler CM, Goldberg TE, Malhotra AK, Pickar D, Breier A (1998) Effects of Ketamine on Thought Disorder, Working Memory, and Semantic Memory in Healthy Volunteers. Biological Psychiatry 43:811-816. Abstract

Baldeweg T, Spence S, Hirsch SR, Gruzelier J (1998) Gamma-band electroencephalographic oscillations in a patient with somatic hallucinations. Lancet 352:620-621. Abstract

Becker C, Gramann K, Muller HJ, Elliott MA (2009) Electrophysiological correlates of flicker-induced color hallucinations. Conscious Cogn 18:266-276. Abstract

Behrendt RP (2003) Hallucinations: synchronisation of thalamocortical gamma oscillations underconstrained by sensory input. Conscious Cogn 12:413-451. Abstract

Buzsaki G (1991) The thalamic clock: emergent network properties. Neuroscience 41:351-364. Abstract

Cadonic C, Albensi BC (2014) Oscillations and NMDA receptors: Their interplay create memories. AIMS Neuroscience 1:52-64.

Caixeta FV, Cornelio AM, Scheffer-Teixeira R, Ribeiro S, Tort AB (2013) Ketamine alters oscillatory coupling in the hippocampus. Sci Rep 3:2348. Abstract

Chrobak JJ, Hinman JR, Sabolek HR (2008) Revealing past memories: proactive interference and ketamine-induced memory deficits. J Neurosci 28:4512-4520. Abstract

Driesen NR, McCarthy G, Bhagwagar Z, Bloch M, Calhoun V, D'souza DC, Gueorguieva R, He G, Ramachandran R, Suckow RF, Anticevic A, Morgan PT, Krystal JH (2013) Relationship of resting brain hyperconnectivity and schizophrenia-like symptoms produced by the NMDA receptor antagonist ketamine in humans. Mol Psychiatry 18:1199-1204. Abstract

Ehrlichman RS, Gandal MJ, Maxwell CR, Lazarewicz MT, Finkel LH, Contreras D, Turetsky BI, Siegel SJ (2009) N-methyl-d-aspartic acid receptor antagonist-induced frequency oscillations in mice recreate pattern of electrophysiological deficits in schizophrenia. Neuroscience 158:705-712. Abstract

Ffytche DH (2008) The hodology of hallucinations. Cortex 44:1067-1083. Abstract

Fond G, Loundou A, Rabu C, Macgregor A, Lancon C, Brittner M, Micoulaud-Franchi JA, Richieri R, Courtet P, Abbar M, Roger M, Leboyer M, Boyer L (2014) Ketamine administration in depressive disorders: a systematic review and meta-analysis. Psychopharmacology (Berl) 231: 3663-3676. Abstract

Hakami T, Jones NC, Tolmacheva EA, Gaudias J, Chaumont J, Salzberg M, O'Brien TJ, Pinault D (2009) NMDA receptor hypofunction leads to generalized and persistent aberrant gamma oscillations independent of hyperlocomotion and the state of consciousness. PLoS One 4:e6755. Abstract

Hetem LA, Danion JM, Diemunsch P, Brandt C (2000) Effect of a sub-anesthetic dose of ketamine on memory and conscious awareness in healthy volunteers. Psychopharmacology (Berl) 152:283-288. Abstract

Hiyoshi T, Kambe D, Karasawa J, Chaki S (2014) Differential effects of NMDA receptor antagonists at lower and higher doses on basal gamma band oscillation power in rat cortical electroencephalograms. Neuropharmacology 85:384-396. Abstract

Homayoun H, Moghaddam B (2007) NMDA receptor hypofunction produces opposite effects on prefrontal cortex interneurons and pyramidal neurons. J Neurosci 27:11496-11500. Abstract

Hong LE, Summerfelt A, Buchanan RW, O'Donnell P, Thaker GK, Weiler MA, Lahti AC (2010) Gamma and delta neural oscillations and association with clinical symptoms under subanesthetic ketamine. Neuropsychopharmacology 35:632-640. Abstract

Hunt MJ, Raynaud B, Garcia R (2006) Ketamine dose-dependently induces high-frequency oscillations in the nucleus accumbens in freely moving rats. Biol Psychiatry 60:1206-1214. Abstract

Kocsis B (2012) Differential role of NR2A and NR2B subunits in N-methyl-D-aspartate receptor antagonist-induced aberrant cortical gamma oscillations. Biol Psychiatry 71:987-995. Abstract

Krystal JH, Karper LP, Seibyl JP, Freeman GK, Delaney R, Bremner JD, Heninger GR, Bowers MB, Jr., Charney DS (1994) Subanesthetic effects of the noncompetitive NMDA antagonist, ketamine, in humans. Psychotomimetic, perceptual, cognitive, and neuroendocrine responses. Arch Gen Psychiatry 51:199-214. Abstract

Kulikova SP, Tolmacheva EA, Anderson P, Gaudias J, Adams BE, Zheng T, Pinault D (2012) Opposite effects of ketamine and deep brain stimulation on rat thalamocortical information processing. Eur J Neurosci 36:3407-3419. Abstract

Llinas RR, Ribary U, Jeanmonod D, Kronberg E, Mitra PP (1999) Thalamocortical dysrhythmia: A neurological and neuropsychiatric syndrome characterized by magnetoencephalography. Proc Natl Acad Sci U S A 96:15222-15227. Abstract

Ma J, Leung LS (2007) The supramammillo-septal-hippocampal pathway mediates sensorimotor gating impairment and hyperlocomotion induced by MK-801 and ketamine in rats. Psychopharmacology (Berl) 191:961-974. Abstract

McGirr A, Berlim MT, Bond DJ, Fleck MP, Yatham LN, Lam RW (2014) A systematic review and meta-analysis of randomized, double-blind, placebo-controlled trials of ketamine in the rapid treatment of major depressive episodes. Psychol Med1-12. Abstract

Molina LA, Skelin I, Gruber AJ (2014) Acute NMDA receptor antagonism disrupts synchronization of action potential firing in rat prefrontal cortex. PLoS One 9:e85842. Abstract

Newcomer JW, Farber NB, Jevtovic-Todorovic V, Selke G, Melson AK, Hershey T, Craft S, Olney JW (1999) Ketamine-induced NMDA receptor hypofunction as a model of memory impairment and psychosis. Neuropsychopharmacology 20:106-118. Abstract

Nicolas MJ, Lopez-Azcarate J, Valencia M, Alegre M, Perez-Alcazar M, Iriarte J, Artieda J (2011) Ketamine-induced oscillations in the motor circuit of the rat basal ganglia. PLoS One 6:e21814. Abstract

Palenicek T, Fujakova M, Brunovsky M, Balikova M, Horacek J, Gorman I, Tyls F, Tislerova B, Sos P, Bubenikova-Valesova V, Hoschl C, Krajca V (2011) Electroencephalographic spectral and coherence analysis of ketamine in rats: correlation with behavioral effects and pharmacokinetics. Neuropsychobiology 63:202-218. Abstract

Pinault D (2008) N-methyl d-aspartate receptor antagonists ketamine and MK-801 induce wake-related aberrant gamma oscillations in the rat neocortex. Biol Psychiatry 63:730-735. Abstract

Pinault (2014) N-methyl D-aspartate receptor antagonists amplify network baseline gamma frequency (30-80 Hz) oscillations: Noise and signal. AIMS Neuroscience 1:169-182.

Rolls ET, Loh M, Deco G, Winterer G (2008) Computational models of schizophrenia and dopamine modulation in the prefrontal cortex. Nat Rev Neurosci 9:696-709. Abstract

Spencer KM, Nestor PG, Perlmutter R, Niznikiewicz MA, Klump MC, Frumin M, Shenton ME, McCarley RW. Neural synchrony indexes disordered perception and cognition in schizophrenia. Proc Natl Acad Sci U S A . 2004 Dec 7 ; 101(49):17288-93. Abstract

Tsuda N, Hayashi K, Hagihira S, Sawa T (2007) Ketamine, an NMDA-antagonist, increases the oscillatory frequencies of alpha-peaks on the electroencephalographic power spectrum. Acta Anaesthesiol Scand 51:472-481. Abstract

Zarate CA, Jr., Singh JB, Carlson PJ, Brutsche NE, Ameli R, Luckenbaugh DA, Charney DS, Manji HK (2006) A randomized trial of an N-methyl-D-aspartate antagonist in treatment-resistant major depression. Arch Gen Psychiatry 63:856-864. Abstract

View all comments by Didier Pinault

Related News: Ketamine Elicits Brain State Resembling Early Stages of Schizophrenia

Comment by:  Alan AnticevicJohn Krystal (SRF Advisor)
Submitted 8 October 2014
Posted 8 October 2014

Linking Hyperconnectivity Induced via Acute Ketamine to Neuronal Mechanisms and Emerging System-Level Markers in Schizophrenia
We sincerely appreciate the recent engaging commentaries focusing on our paper. The constructive and thoughtful discussion has raised a number of important issues regarding the ketamine model in schizophrenia research. In particular, in the latest commentary Dr. Pinault has noted several hypotheses regarding our findings on which we would like to further comment.

First, what does the observed "hyperconnectivity" represent functionally? Does this "signature" relate to alterations in excitation (E) and inhibition (I) balance in cortical circuits and in turn reflect an elevation in shared signal between prefrontal areas in our analyses? It is important to note that the reported effect builds on basic preclinical studies and studies examining cortical metabolism, which have established that NMDAR antagonism elevates pyramidal cell activity (Moghaddam and Adams, 1998), extracellular glutamate levels (Homayoun and Moghaddam, 2007), cortical metabolism (Breier et al., 1997; Lahti et al., 1995; Lahti et al., 2001; Vollenweider et al., 1997; Vollenweider et al., 2000), and resting-state functional connectivity (Driesen et al., 2013; Pinault, 2008; Driesen et al., 2013). Moreover, a recent influential study by Schobel and colleagues demonstrated that NMDAR antagonism caused elevated "spreading" of hippocampal activation and metabolism (Schobel et al., 2013). Strikingly, they showed that repeated NMDAR antagonist dosing eventually caused chronic hippocampal atrophy, resembling observations after longer periods of illness. A possible corollary of this preclinical finding suggests that aberrant increases in excitation, and perhaps connectivity induced by NMDAR antagonism, are likely pathological. Therefore, the "hyperconnectivity" pattern may reflect increased pyramidal cell excitability, reduced pyramidal input selectivity, or other sources of aberrant cortical hypersynchrony.

One mechanism could involve reductions in the inhibitory component of cortical connectivity, which may alter excitatory connections. It is possible that such deficits not only increase excitability, but also reduce the input selectivity of cortical excitation (i.e., pathologically increase cortical functional connectivity). It will be critical for future studies to establish whether the observed "hyperconnectivity" measured via BOLD fMRI also relates to concurrently abnormal oscillations measured via EEG and in what frequency band. We comment on this specific issue below. Relatedly, follow-up clinical and pharmacological investigations should more carefully decompose the "correlation" measures between pairwise regions by considering both shared and unshared signal components (Friston, 2011). Put differently, it will be critical to show that the alterations in BOLD functional connectivity measures actually reflect elevations in aberrant shared signal (not just alterations in the variance structure), which could also be altered in schizophrenia (Yang et al., 2014). Pinpointing the precise nature of signal alteration that induces "hyperconnectivity" will have key implications for interpreting this effect and, in turn, for treatment studies designed to reverse this effect.

Second, what might be the precise synaptic contributions to such aberrant "hyperconnectivity"? Dr. Pinault elegantly argues for the role of GABAergic interneurons in the reported effect. We are in full agreement here; a number of studies have implicated interneurons as playing a key role in the effects of NMDAR antagonists (Krystal and Moghaddam, 2011; Krystal et al., 1994; Krystal et al., 2003; Anticevic et al., 2012). It remains unknown, however, which interneuron subtype is predominantly involved in their effects. We posit that the combination of preclinical animal work and computational modeling approaches is well positioned to address this question. For instance, studies that carefully experimentally dissect the potential contributions of specific neuronal subtypes to the observed "hyperconnectivity" pattern will be important to constrain our mechanistic understanding of acute NMDAR antagonist effects on cortical microcircuits (Kwan and Dan, 2012). Similarly, computational studies that incorporate multiple interneuron subtypes will help generate predictions for both electrophysiological and functional connectivity experiments that can be tested in animals and humans (Lisman et al., 2010; Lisman, 2012). It is well established that there are two broad classes of interneurons—fast-spiking cells that are critical for gamma oscillations and slower-spiking cells that strongly contribute to theta oscillations (Lisman, 2012). As noted, it remains unknown which GABAergic interneuron contribution "drives" the hyperconnectivity and at which frequency band (i.e., gamma or theta). It is demonstrated that systemic ketamine administration attenuates theta power but concurrently increases gamma power in mice (Ehrlichman et al., 2009; Lazarewicz et al., 2010), rats (Sabolek, H., et al., 2006), and humans (Hong et al., 2010). Computational simulations established that manipulating NMDAR currents on slow-spiking GABAergic cells (as opposed to fast-spiking cells) captured these dissociable gamma/theta experimental observations in silico (Neymotin et al., 2011). Forthcoming computational studies should strive to extend such micro-circuit models to capture neural system-level connectivity alterations in schizophrenia and following pharmacological challenge (Anticevic et al., 2013). In turn, these computational models can generate cell-specific predictions for NMDAR antagonist effects that can be tested experimentally, both preclinically and in human neuroimaging studies (Kwan and Dan, 2012).

Third, is there a dose effect of acute NMDAR antagonists? We believe that there might be a dose effect, which needs to be carefully considered when interpreting present effects—as argued by Dr. Pinault. Perhaps cognitive activation studies can speak to this issue. For instance, in a recent related study, we found that acute NMDAR antagonism in humans reduced cognitive performance—namely delayed spatial working memory (WM) by preferentially increasing error rates to non-target probes at specific spatial locations that were proximal to original WM locations (Murray et al., 2014). Put differently, volunteers administered ketamine were more likely to report a false alarm than report a memory at a location that they had not previously seen (a miss). We qualitatively and quantitatively captured this effect in our computational model by mildly reducing NMDAR drive onto inhibitory cells in the model—effectively inducing disinhibition and a "blurring" of the WM representation (Murray et al., 2014). The model performance mimicked that of healthy human volunteers at low levels of NMDAR antagonism but not at higher levels, where recurrent excitation on pyramidal cells was also reduced (Wang et al., 2013).

In a related animal study, Arnsten and colleagues examined effects of acute ketamine administration in monkeys during performance of a similar delayed spatial WM task (Wang et al., 2013). In their experiment the animals produced random saccades at previously unseen probe locations (i.e., misses), suggesting a complete loss of memory representation, accompanied by reduced delay-related firing of prefrontal neurons. In our computational simulations we were able to capture both behavioral results as reflecting distinct levels of NMDAR antagonism. In that sense, it may be the case that distinct dose-dependent levels of NMDAR antagonism produce different E/I balance regimes. Put differently, at higher doses of ketamine, where both the inhibitory and excitatory NMDAR synaptic components are affected, the "hyperconnectivity" regime may be replaced by functional connectivity reductions—a hypothesis that needs systematic experimental testing in animals. Therefore, we argue for the importance of carefully dissecting the dose-dependent contributions of ketamine on both behavior and functional connectivity in humans.

Fourth, how might the prefrontal "hyperconnectivity" effect relate to emerging "thalamo-cortical" markers of schizophrenia? An excellent observation in Dr. Pinault's commentary raises the importance of linking the observed "hyperconnectivity," which may possibly reflect alterations in gamma-band oscillations, to the thalamo-cortical gating abnormalities that underlie many theoretical models of schizophrenia (Andreasen, 1997). Unifying these effects constitutes an important theoretical and experimental goal in light of several recent empirical reports showing elevated sensory-thalamic functional connectivity in chronic schizophrenia patients (Woodward et al., 2012; Klingner et al., 2014; Anticevic et al., 2013). It may be the case that NMDAR antagonism "elevates" this sensory-thalamic coupling, either by decreasing the gamma signal-to-noise ratio or possibly by affecting the prefrontal "top-down" control aspect of sensory-thalamic information flow. These scenarios remain to be systematically tested.

In addition, it will be important to establish whether the thalamo-cortical disconnectivity in schizophrenia also exhibits functional dissociations along illness stages or appears during initial illness onset, as reported here for prefrontal hyperconnectivity. In that sense, some neural markers may show "dynamic" change along illness stages or perhaps reflect state-dependent functional causes (e.g., transient symptom exacerbation), whereas other functional connectivity markers may reflect a "trait-like" signature that persists across the illness course. Further establishing how the ketamine model maps onto these distinct neural signatures across illness stages and functional states represents a key goal for harnessing the ketamine model for targeted drug development for schizophrenia.

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