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S.07.05 Abnormalities in reward prediction error signals in depression and schizophrenia
S.07. Young Scientists Award symposium 2 London and Maudsley NHS Foundation Trust and the Institute of Psychiatry, King’s College London (NIHR, Department of Health, UK). However, the funders had no role in the design and conduct of the study, or in data collection, analysis, interpretation or writing of this report. References [1] Kirchheiner, J., Nickchen, K., Bauer, M., Wong, M.L., Licinio, J., Roots, I. et al. 2004 Pharmacogenetics of antidepressants and antipsychotics: the contribution of allelic variations to the phenotype of drug response. Mol Psychiatry; 9(5):442–473. [2] Uher, R., Maier, W., Hauser, J., Marusic, A., Schmael, C., Mors, O. et al. 2009 Differential efficacy of escitalopram and nortriptyline on dimensional measures of depression. Br J Psychiatry; 194(3):252–259.
S.07.05 Abnormalities in reward prediction error signals in depression and schizophrenia V. Gradin1 ° , P. Kumar2 , G. Waiter3 , T. Ahearn3 , I. Reid4 , 1 University C. Stickle5 , M. Milders6 , J. Hall7 , J.D. Steele8 . of Aberdeen, Mental Health, Aberdeen Scotland, United Kingdom; 2 University of Oxford, Department of Psychiatry, Oxford, United Kingdom; 3 University of Aberdeen, Department of radiology, Aberdeen, United Kingdom; 4 University of Aberdeen, Mental Health, Aberdeen, United Kingdom; 5 Cornhill Hospital, Mental Health, Aberdeen, United Kingdom; 6 University of Aberdeen, Department of Psychology, Aberdeen, United Kingdom; 7 University of Edinburgh, Department of Psychiatry, Edinburgh, United Kingdom; 8 University of Dundee, Centre of Neuroscience, Dundee, United Kingdom Abnormal functioning of the dopamine (DA) system has been linked to anhedonia in depression and negative plus positive symptoms in schizophrenia. It remains unclear though, how a DA dysfunction could mechanistically link to symptoms. “Phasic” DA signals code a reward prediction error that may mediate learning of stimulus-response-outcomes associations and/or attribution of incentive salience to stimuli. Temporal difference (TD) models provide a mathematical description of these signals [1]. Abnormalities of DA signals in depression/schizophrenia could relate to anhedonia/negative symptoms, and also to psychotic symptoms by contributing to abnormal associations. Depression, schizophrenia and a control groups, were scanned using fMRI during an instrumental reward-learning task. A TD model was used to generate a reward-learning signal that was used for image analysis. Depressive patients demonstrated reduced TD signals in the midbrain and striatum compared to controls. Schizophrenic patients demonstrated reduced activation in the caudate, insula and amygdala-hippocampus compared to controls and increased activation in the striatum compared to depressed patients. In schizophrenia, decreased activation in the midbrain, insula and amygdala-hippocampus correlated with increased severity of psychotic symptoms. In depression, decreased activation in the striatum and midbrain correlated with increased anhedonia symptoms. Diminished reward-related DA signals in depression/schizophrenia are consistent with anhedonia/negative symptoms [2]. In schizophrenia, abnormal DA signals may be associated with psychotic symptoms by attributing aberrant salience to stimuli [3]. These results may help to bridge the gap between the biology and phenomenology of the illnesses and highlight the potential role of abnormalities of phasic signals as biomarkers of psychiatric disorders.
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References [1] Montague P.R., Dayan P., Sejnowski T.J., 1996 A framework for Mesencephalic Dopamine Systems Based on Predictive Hebbian Learning. The Journal of Neuroscience 16(5), 1936–1947. [2] Kumar P., Waiter G., Ahearn T., Milders M., Reid I., Steele J.D. 2008 Abnormal temporal difference reward-learning signals in major depression. Brain 131(8), 2084–2093. [3] Kapur S., 2003 Psychosis as a State of Aberrant Salience: A Framework Linking Biology, Phenomenology, and Pharmacology in Schizophrenia. American Journal of Psychiatry 160, 13−23.
S.07.06 Netrin G1 polymorphisms in cocaine and alcohol codependence vulnerability: from mice to men S. Kelai1 ° , G. Maussion1 , N. Munoz1 , C. Boni1 , N. Ramoz1 , M. Simonneau1 , P. Gorwood1 . 1 Centre de Psychiatrie et de Neurosciences, Inserm U894, Paris, France Addiction is a complex disease inducing changes in synaptic plasticity where netrins G1 (ntng1) could play a major part as it has an important role in the development of central nervous system, particularly, in axonal guidance, signalling and glutamate NMDA receptor function [1]. The aim of our study was to decipher the role of netrin G1 in an early stage of cocaine addiction development in mice and to explore human NTNG1 polymorphisms in drug addiction. Microarray analysis of laser-captured nucleus accumbens (Nac) showed 46 up-regulated and 162 down-regulated genes by cocaine place preference. We have selected NTNG1 gene, which seemed to be relevant, because it was highly represented on the microarray (13 probes) giving strong evidence for results.. Furthermore, quantitative-PCR measurements confirmed NTNG1 down-regulation found in microarray experiments. Thereafter, we genotyped NTNG1 gene in the Collaborative Studies on Genetics of Alcoholism (COGA cohort from National Institute on Alcohol Abuse and Alcoholism, 709 subjects for a total of 146 families with several members affected by alcoholism and/or other drugs of abuse like cocaine, cannabis, opioids and with exhaustive clinical phenotypes). Two of them (rs597332 and rs503828) were found associated only with co-dependence to alcohol and cocaine. Our animal model allowed us to identify new specific genes underlying vulnerability to addiction. Our data showed for the first time evidence that NTNG1 could play a major role in polysubstances addiction. Further investigations are needed to understand how drug of abuse could change NTNG1 expression, and if some particular human endophenotypes could explain our results. Disclosure statement: This work was supported by the Institut de Recherches Scientifiques sur les boissons (IREB) and the Mission Interminist´erielle de Lutte contre les Drogues et Toxicomanies (MILDT). Sabah Kelai was a recipient of grants from R´egion Ile de France (Neuropole de Recherche Francilien, Nerf). References [1] Kim S, Burette A, Chung HS, Kwon SK, Woo J, Lee HW, Kim K, Kim H, Weinberg RJ, Kim E. NGL family PSD-95-interacting adhesion molecules regulate excitatory synapse formation. Nat Neurosci. 2006, 9(10):1294–301.
S.07.05 Abnormalities in reward prediction error signals in depression and schizophrenia V. Gradin1 ° , P. Kumar2 , G. Waiter3 , T. Ahearn3 , I. Reid4 , 1 University C. Stickle5 , M. Milders6 , J. Hall7 , J.D. Steele8 . of Aberdeen, Mental Health, Aberdeen Scotland, United Kingdom; 2 University of Oxford, Department of Psychiatry, Oxford, United Kingdom; 3 University of Aberdeen, Department of radiology, Aberdeen, United Kingdom; 4 University of Aberdeen, Mental Health, Aberdeen, United Kingdom; 5 Cornhill Hospital, Mental Health, Aberdeen, United Kingdom; 6 University of Aberdeen, Department of Psychology, Aberdeen, United Kingdom; 7 University of Edinburgh, Department of Psychiatry, Edinburgh, United Kingdom; 8 University of Dundee, Centre of Neuroscience, Dundee, United Kingdom Abnormal functioning of the dopamine (DA) system has been linked to anhedonia in depression and negative plus positive symptoms in schizophrenia. It remains unclear though, how a DA dysfunction could mechanistically link to symptoms. “Phasic” DA signals code a reward prediction error that may mediate learning of stimulus-response-outcomes associations and/or attribution of incentive salience to stimuli. Temporal difference (TD) models provide a mathematical description of these signals [1]. Abnormalities of DA signals in depression/schizophrenia could relate to anhedonia/negative symptoms, and also to psychotic symptoms by contributing to abnormal associations. Depression, schizophrenia and a control groups, were scanned using fMRI during an instrumental reward-learning task. A TD model was used to generate a reward-learning signal that was used for image analysis. Depressive patients demonstrated reduced TD signals in the midbrain and striatum compared to controls. Schizophrenic patients demonstrated reduced activation in the caudate, insula and amygdala-hippocampus compared to controls and increased activation in the striatum compared to depressed patients. In schizophrenia, decreased activation in the midbrain, insula and amygdala-hippocampus correlated with increased severity of psychotic symptoms. In depression, decreased activation in the striatum and midbrain correlated with increased anhedonia symptoms. Diminished reward-related DA signals in depression/schizophrenia are consistent with anhedonia/negative symptoms [2]. In schizophrenia, abnormal DA signals may be associated with psychotic symptoms by attributing aberrant salience to stimuli [3]. These results may help to bridge the gap between the biology and phenomenology of the illnesses and highlight the potential role of abnormalities of phasic signals as biomarkers of psychiatric disorders.
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References [1] Montague P.R., Dayan P., Sejnowski T.J., 1996 A framework for Mesencephalic Dopamine Systems Based on Predictive Hebbian Learning. The Journal of Neuroscience 16(5), 1936–1947. [2] Kumar P., Waiter G., Ahearn T., Milders M., Reid I., Steele J.D. 2008 Abnormal temporal difference reward-learning signals in major depression. Brain 131(8), 2084–2093. [3] Kapur S., 2003 Psychosis as a State of Aberrant Salience: A Framework Linking Biology, Phenomenology, and Pharmacology in Schizophrenia. American Journal of Psychiatry 160, 13−23.
S.07.06 Netrin G1 polymorphisms in cocaine and alcohol codependence vulnerability: from mice to men S. Kelai1 ° , G. Maussion1 , N. Munoz1 , C. Boni1 , N. Ramoz1 , M. Simonneau1 , P. Gorwood1 . 1 Centre de Psychiatrie et de Neurosciences, Inserm U894, Paris, France Addiction is a complex disease inducing changes in synaptic plasticity where netrins G1 (ntng1) could play a major part as it has an important role in the development of central nervous system, particularly, in axonal guidance, signalling and glutamate NMDA receptor function [1]. The aim of our study was to decipher the role of netrin G1 in an early stage of cocaine addiction development in mice and to explore human NTNG1 polymorphisms in drug addiction. Microarray analysis of laser-captured nucleus accumbens (Nac) showed 46 up-regulated and 162 down-regulated genes by cocaine place preference. We have selected NTNG1 gene, which seemed to be relevant, because it was highly represented on the microarray (13 probes) giving strong evidence for results.. Furthermore, quantitative-PCR measurements confirmed NTNG1 down-regulation found in microarray experiments. Thereafter, we genotyped NTNG1 gene in the Collaborative Studies on Genetics of Alcoholism (COGA cohort from National Institute on Alcohol Abuse and Alcoholism, 709 subjects for a total of 146 families with several members affected by alcoholism and/or other drugs of abuse like cocaine, cannabis, opioids and with exhaustive clinical phenotypes). Two of them (rs597332 and rs503828) were found associated only with co-dependence to alcohol and cocaine. Our animal model allowed us to identify new specific genes underlying vulnerability to addiction. Our data showed for the first time evidence that NTNG1 could play a major role in polysubstances addiction. Further investigations are needed to understand how drug of abuse could change NTNG1 expression, and if some particular human endophenotypes could explain our results. Disclosure statement: This work was supported by the Institut de Recherches Scientifiques sur les boissons (IREB) and the Mission Interminist´erielle de Lutte contre les Drogues et Toxicomanies (MILDT). Sabah Kelai was a recipient of grants from R´egion Ile de France (Neuropole de Recherche Francilien, Nerf). References [1] Kim S, Burette A, Chung HS, Kwon SK, Woo J, Lee HW, Kim K, Kim H, Weinberg RJ, Kim E. NGL family PSD-95-interacting adhesion molecules regulate excitatory synapse formation. Nat Neurosci. 2006, 9(10):1294–301.