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Gene-gene interactions in explaining heritability estimates for psychotic illness: modelling epistasis
S.32. Translational models must reflect evolving concepts of psychosis: from psychopathology to pathobiology on conclusions made regarding predictability of preclinical models and/or quality of drug targets for evaluation in clinical proof-ofconcept studies. Higher failure rates due to non-reliable scientific data increase the risks and costs associated with Research and Development (R&D) and may hamper the successful translation of innovation to novel treatments for patients. Many factors may contribute to this situation, including technical/methodological, cultural and educational aspects. There is a need for simple, sustainable solutions that facilitate data quality without impacting innovation and freedom of research. To address the issues of preclinical data quality a number of initiatives have been initiated, both within pharmaceutical companies and with pharmaceutical companies being part of research and/or quality networks and international consortia. In this presentation, I will highlight the issues from a view of the industry and provide an overview of some of the initiatives that aim to address those issues, including strategies followed by individual companies, academic groups engaging in drug development, and some of the consorted approaches. Disclosure statement: Thomas Steckler is an employee of Janssen Research & Development.
S.31.02 Generalizability to man: how to use comparable readouts preclinically and in patients M. Kas1 ° 1 Rudolf Magnus Institute of Neuroscience, Utrecht, The Netherlands Developing etiology-directed therapeutics for neuropsychiatric disorders requires integrated cross-species experimental approaches and should focus on quantitative biological parameters. However, current nosology for the diagnosis of neuropsychiatric disorders is not based on their underlying etiology but on convention based clustering of qualitative symptoms of the disorder. While these diagnostic categories are sufficient to provide the basis for general clinical management, they do not describe the underlying neurobiology that gives rise to individual neuropsychiatric symptoms. The ability to precisely link these symptoms to underlying neurobiology would not only facilitate the development of better treatments, it would also allow physicians to provide patients with a better understanding of the complexities and management of their illness. To realize this ambition, a paradigm shift is needed to raise awareness and to build an understanding of how neuropsychiatric diagnoses can be based on quantitative biological parameters that can be back translated to pre-clinical models. The main difficulty in the construction of biologically valid diagnoses is the lack of objective biomarkers. Moreover, the uncertain relationship between diagnosis and underlying etiology has created difficulties for etiological research and made the generation of appropriate disease models and development of targeted treatments difficult. This presentation addresses that preclinical data are part of the integrated experimental approach where each approach brings forward different levels of human relevance, mechanistic insights, and throughput. In addition, these integrated crossspecies approaches should take into account species specificity, genetic background variation, phenotype robustness, evolutionary conserved processes, construct validity, neuronal biomarkers of target engagement, and developmental stages.
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S.32. Translational models must reflect evolving concepts of psychosis: from psychopathology to pathobiology S.32.01 Modelling complex pathologies or more simple endophenotypes? P.M. Moran1 ° 1 Nottingham University, School of Psychology, Nottingham, United Kingdom Following a period of frustration with genetic approaches Genome Wide Association Studies (GWAS) of schizophrenia have suggested potential for new therapeutic targets. These have given renewed cause for optimism about the possibility of using genetic approaches to identify novel biological treatment targets for schizophrenia. However this creates a need for model biological systems in which to test them preclinically, coinciding with a period of disillusionment about how well animal models predict translation to the clinic. In the following I discuss how consideration of psychiatric symptoms in terms of Research Domain Criteria (RDoC) suggest new directions for future translational modelling. While such approaches better represent the complexity of behavioural and biological phenotypes simple phenotypes are also required to test drug effects in specific brain circuitry. I will discuss the concept of abnormal salience allocation as an explanatory framework for psychosis. This construct has evolved from psychopathological and pathobiological experiments in both animals and humans. Combining complex behavioural, pharmacological and genetic approaches in mice we have shown that while the dopamine D2 receptor can be necessary for antipsychotics to enhance salience allocation, there is an as yet unidentified dopamine D2 receptor independent mechanism only unmasked in the presence of D-amphetamine [1,2]. Data in mice further suggest antipsychotics may act specifically on salience allocation influenced by prior knowledge rather than salience influenced by physical properties of stimuli. Translational modelling approaches such as these can provide insight into understanding current treatments, refine theoretical perspectives on psychopathology and potentially help to identify novel therapeutic targets. References [1] Bay-Richter, C., O’Callaghan, M.J., Mathur, N., O’Tuathaigh, C.M., Heery, D.M., Fone, K.C., Waddington J.L., Moran, P.M. 2013. D-amphetamine and antipsychotic drug effects on latent inhibition in mice lacking dopamine D2 receptors. Neuropsychopharmacology 38, 1512–1520. [2] O’Callaghan M.J., Bay-Richter C., O’Tuathaigh C.M.P., Heery D.M., Waddington J.L. and Moran P.M. 2014. Dopamine D2 but not Dopamine D1 receptor is necessary for the enhancement of latent inhibition by clozapine and haloperidol in mice. Journal of Psychopharmacology 28, 973−7.
S.32.03 Gene-gene interactions in explaining heritability estimates for psychotic illness: modelling epistasis J.L. Waddington1 ° , C.M. O’Tuathaigh2 1 Royal College of Surgeons in Ireland, Molecular and Cellular Therapeutics, Dublin 2, Ireland; 2 University College Cork, Department of Medicine, Cork, Ireland The most recent genome-wide association study of schizophrenia has identified 108 loci. However, such diversity can account
S154
S.33. Phenotype-genotype interactions in developmental disorders
only for a minority of the heritability estimate, with this gap being termed the ‘missing heritability’ of schizophrenia. One explanation is that individual genes interact with each other (epistasis). This phenomenon can now be studied in mice mutant for schizophrenia risk genes. We have generated male and female mutants with simultaneous disruption of either or both of the schizophrenia risk genes Disrupted-in-Schizophrenia 1 (DISC1) and neuregulin 1 (NRG1) by intercrossing mice with disruption of transmembrane domain (TM)-NRG1 and mice with mutation in exon 2 of DISC1. This was followed by phenotypic evaluation of all resultant genotype-wildtype combinations, to allow resolution of those phenotypes subject to epistatic regulation from those for which DISC1 and NRG1 exert independent, additive, or no effects. NRG1 mutants exhibited age-specific hyperactivity in adulthood, in a manner unrelated to DISC1 genotype, while DISC1 mutants did not show hyperactivity; thus, NRG1 phenotype was unaltered by co-disruption of DISC1, indicating no epistasis. Neither disruption of DISC1 or NRG1 alone nor or co-disruption of both genes resulted in impairment in spatial working memory, indicating no individual mutant phenotypes or epistasis. In contrast, while disruption of either NRG1 or DISC1 alone was without effect on sociability, co-disruption of DISC1 and NRG1 abolished sociability, indicating a prominent epistatic effect. Epistasis may be an important component of genetic risk for domains of psychotic illness. S.32.04 Cell type-specific convergent pathways underlie gene-environment interaction in psychotic disorders A. Kamiya1 ° 1 Johns Hopkins University School of Medicine, Psychiatry and Behavioral Sciences, Baltimore, USA Multiple adverse environmental factors contribute to the pathogenesis of schizophrenia via complex interactions with genetic risk factors in susceptible individuals. We have been modeling complex etiologically relevant gene-environment interactions in mice that selectively express mutant Disrupted-In-Schizophrenia 1 (DISC1) in neurons or astrocytes and are exposed to prenatal immune activation or environmental toxins, or cannabis during adolescence. We evaluated the neurobehavioral, histopathological, neuroimmune, and molecular phenotypes in adult mice. We found that mice with neuronal expression of mutant DISC1 developed the brain and behavioral alterations consistent with aspects of mood disorders following prenatal immune activation [1], and schizophrenia-like abnormalities treatable with D-serine treatment following developmental exposure to low doses of Pb2+ [2]. Chronic adolescent cannabis (tetrahydrocannabinol) exposure of mice expressing mutant DISC1 in neurons exacerbated deficient fear conditioning and synergistically decreased c-Fos expression induced by cue-dependent fear memory retrieval [3]. The similar adolescent cannabis exposure in mice expressing mutant DISC1 in astrocytes led to lasting cognitive impairment and decreased numbers of parvalbumin-positive neurons in adult mice. These behavioral and neuroanatomical changes were restored in DISC1 mice after doxycycline treatment to shut down expression of mutant DISC1, indicating that expression of this risk factor was necessary for adolescent cannabis to produce the clinical manifestations in adulthood. Our studies suggest that both shared and cell type specific alterations could explain variable phenotypic manifestations of gene-environment interactions consistent with symptom heterogeneity of psychotic disorders [4].
References [1] Abazyan B, Nomura J, Kannan G, Ishizuka K, Tamashiro KL, Nucifora F, Pogorelov V, Ladenheim B, Yang C, Krasnova IN, Cadet JL, Pardo C, Mori S, Kamiya A, Vogel MW, Sawa A, Ross CA, Pletnikov MV. Prenatal interaction of mutant DISC1 and immune activation produces adult psychopathology. Biol Psychiatry. 2010 Dec 15; 68(12): 1172−81. [2] Abazyan B, Dziedzic J, Hua K, Abazyan S, Yang C, Mori S, Pletnikov MV, Guilarte TR. Chronic exposure of mutant DISC1 mice to lead produces sex-dependent abnormalities consistent with schizophrenia and related mental disorders: a gene-environment interaction study. Schizophr Bull. 2014 May; 40(3): 575−84. [3] Ballinger MD, Saito A, Abazyan B, Taniguchi Y, Huang CH, Ito K, Zhu X, Segal H, Jaaro-Peled H, Sawa A, Mackie K, Pletnikov MV, Kamiya A. Adolescent cannabis exposure interacts with mutant DISC1 to produce impaired adult emotional memory. Neurobiol Dis. 2015 Oct; 82: 176−84. [4] Ayhan Y, McFarland R, Pletnikov MV. Animal models of geneenvironment interaction in schizophrenia: A dimensional perspective. Prog Neurobiol. 2016 Jan; 136: 1−27.
S.33. Phenotype-genotype interactions in developmental disorders S.33.02 Is it possible to reduce phenotypic heterogeneity in a biological meaningful way? A.M. Persico1 ° 1 University of Messina, Child and Adolescent Neuropsychiatry, Messina, Italy The biological components of pathogenetic processes leading to psychopathology are far less numerous than its many triggers, as these converge downstream upon a relatively limited number of mechanisms and pathways, whether be causal or predisposing. A paradigmatic examples is represented by Autism Spectrum Disorder (ASD), a heterogeneous and severe disorder with onset during early childhood and typically a life-time persistent course. The majority of ASD cases stems from complex, “multiplehit”, oligogenic/polygenic contributions involving several loci, together with variable gene-environment interactions and immune abnormalities. These multiple layers of complexity require diagnostic and prognostic biomarker sets collecting information from multiple levels of an individual’s biology, ranging from basic genetics to cognitive processing [1]. Within this framework, unbiased metabolomic analysis offers a sensitive tool to search for urinary metabolite profiles potentially usable as biomarkers for neurodevelopmental disorders. Young ASD children (N = 30, age 2−7) significantly differ from matched controls especially in tryptophan and purine metabolic pathways [2], largely overlapping with results found in rodent models of ASD following maternal immune activation or genetic manipulations [3]. These metabolic abnormalities could underlie several comorbidities frequently associated with ASD, such as seizures, sleep disorders, and gastrointestinal symptoms, and could contribute to autism severity. The potential association between urinary metabolomic patterns, clinical comorbidities and behavioral abnormalities is being investigated. Merging of this information with genetic, electrophysiological and brain imaging data is predicted to maximize validity and predictive power. References [1] Ruggeri B, Sarkans U, Schumann G, Persico AM. Biomarkers in autism spectrum disorder: the old and the new. Psychopharmacology (Berl) 2014; 231:1001–1016.
S.31.02 Generalizability to man: how to use comparable readouts preclinically and in patients M. Kas1 ° 1 Rudolf Magnus Institute of Neuroscience, Utrecht, The Netherlands Developing etiology-directed therapeutics for neuropsychiatric disorders requires integrated cross-species experimental approaches and should focus on quantitative biological parameters. However, current nosology for the diagnosis of neuropsychiatric disorders is not based on their underlying etiology but on convention based clustering of qualitative symptoms of the disorder. While these diagnostic categories are sufficient to provide the basis for general clinical management, they do not describe the underlying neurobiology that gives rise to individual neuropsychiatric symptoms. The ability to precisely link these symptoms to underlying neurobiology would not only facilitate the development of better treatments, it would also allow physicians to provide patients with a better understanding of the complexities and management of their illness. To realize this ambition, a paradigm shift is needed to raise awareness and to build an understanding of how neuropsychiatric diagnoses can be based on quantitative biological parameters that can be back translated to pre-clinical models. The main difficulty in the construction of biologically valid diagnoses is the lack of objective biomarkers. Moreover, the uncertain relationship between diagnosis and underlying etiology has created difficulties for etiological research and made the generation of appropriate disease models and development of targeted treatments difficult. This presentation addresses that preclinical data are part of the integrated experimental approach where each approach brings forward different levels of human relevance, mechanistic insights, and throughput. In addition, these integrated crossspecies approaches should take into account species specificity, genetic background variation, phenotype robustness, evolutionary conserved processes, construct validity, neuronal biomarkers of target engagement, and developmental stages.
S153
S.32. Translational models must reflect evolving concepts of psychosis: from psychopathology to pathobiology S.32.01 Modelling complex pathologies or more simple endophenotypes? P.M. Moran1 ° 1 Nottingham University, School of Psychology, Nottingham, United Kingdom Following a period of frustration with genetic approaches Genome Wide Association Studies (GWAS) of schizophrenia have suggested potential for new therapeutic targets. These have given renewed cause for optimism about the possibility of using genetic approaches to identify novel biological treatment targets for schizophrenia. However this creates a need for model biological systems in which to test them preclinically, coinciding with a period of disillusionment about how well animal models predict translation to the clinic. In the following I discuss how consideration of psychiatric symptoms in terms of Research Domain Criteria (RDoC) suggest new directions for future translational modelling. While such approaches better represent the complexity of behavioural and biological phenotypes simple phenotypes are also required to test drug effects in specific brain circuitry. I will discuss the concept of abnormal salience allocation as an explanatory framework for psychosis. This construct has evolved from psychopathological and pathobiological experiments in both animals and humans. Combining complex behavioural, pharmacological and genetic approaches in mice we have shown that while the dopamine D2 receptor can be necessary for antipsychotics to enhance salience allocation, there is an as yet unidentified dopamine D2 receptor independent mechanism only unmasked in the presence of D-amphetamine [1,2]. Data in mice further suggest antipsychotics may act specifically on salience allocation influenced by prior knowledge rather than salience influenced by physical properties of stimuli. Translational modelling approaches such as these can provide insight into understanding current treatments, refine theoretical perspectives on psychopathology and potentially help to identify novel therapeutic targets. References [1] Bay-Richter, C., O’Callaghan, M.J., Mathur, N., O’Tuathaigh, C.M., Heery, D.M., Fone, K.C., Waddington J.L., Moran, P.M. 2013. D-amphetamine and antipsychotic drug effects on latent inhibition in mice lacking dopamine D2 receptors. Neuropsychopharmacology 38, 1512–1520. [2] O’Callaghan M.J., Bay-Richter C., O’Tuathaigh C.M.P., Heery D.M., Waddington J.L. and Moran P.M. 2014. Dopamine D2 but not Dopamine D1 receptor is necessary for the enhancement of latent inhibition by clozapine and haloperidol in mice. Journal of Psychopharmacology 28, 973−7.
S.32.03 Gene-gene interactions in explaining heritability estimates for psychotic illness: modelling epistasis J.L. Waddington1 ° , C.M. O’Tuathaigh2 1 Royal College of Surgeons in Ireland, Molecular and Cellular Therapeutics, Dublin 2, Ireland; 2 University College Cork, Department of Medicine, Cork, Ireland The most recent genome-wide association study of schizophrenia has identified 108 loci. However, such diversity can account
S154
S.33. Phenotype-genotype interactions in developmental disorders
only for a minority of the heritability estimate, with this gap being termed the ‘missing heritability’ of schizophrenia. One explanation is that individual genes interact with each other (epistasis). This phenomenon can now be studied in mice mutant for schizophrenia risk genes. We have generated male and female mutants with simultaneous disruption of either or both of the schizophrenia risk genes Disrupted-in-Schizophrenia 1 (DISC1) and neuregulin 1 (NRG1) by intercrossing mice with disruption of transmembrane domain (TM)-NRG1 and mice with mutation in exon 2 of DISC1. This was followed by phenotypic evaluation of all resultant genotype-wildtype combinations, to allow resolution of those phenotypes subject to epistatic regulation from those for which DISC1 and NRG1 exert independent, additive, or no effects. NRG1 mutants exhibited age-specific hyperactivity in adulthood, in a manner unrelated to DISC1 genotype, while DISC1 mutants did not show hyperactivity; thus, NRG1 phenotype was unaltered by co-disruption of DISC1, indicating no epistasis. Neither disruption of DISC1 or NRG1 alone nor or co-disruption of both genes resulted in impairment in spatial working memory, indicating no individual mutant phenotypes or epistasis. In contrast, while disruption of either NRG1 or DISC1 alone was without effect on sociability, co-disruption of DISC1 and NRG1 abolished sociability, indicating a prominent epistatic effect. Epistasis may be an important component of genetic risk for domains of psychotic illness. S.32.04 Cell type-specific convergent pathways underlie gene-environment interaction in psychotic disorders A. Kamiya1 ° 1 Johns Hopkins University School of Medicine, Psychiatry and Behavioral Sciences, Baltimore, USA Multiple adverse environmental factors contribute to the pathogenesis of schizophrenia via complex interactions with genetic risk factors in susceptible individuals. We have been modeling complex etiologically relevant gene-environment interactions in mice that selectively express mutant Disrupted-In-Schizophrenia 1 (DISC1) in neurons or astrocytes and are exposed to prenatal immune activation or environmental toxins, or cannabis during adolescence. We evaluated the neurobehavioral, histopathological, neuroimmune, and molecular phenotypes in adult mice. We found that mice with neuronal expression of mutant DISC1 developed the brain and behavioral alterations consistent with aspects of mood disorders following prenatal immune activation [1], and schizophrenia-like abnormalities treatable with D-serine treatment following developmental exposure to low doses of Pb2+ [2]. Chronic adolescent cannabis (tetrahydrocannabinol) exposure of mice expressing mutant DISC1 in neurons exacerbated deficient fear conditioning and synergistically decreased c-Fos expression induced by cue-dependent fear memory retrieval [3]. The similar adolescent cannabis exposure in mice expressing mutant DISC1 in astrocytes led to lasting cognitive impairment and decreased numbers of parvalbumin-positive neurons in adult mice. These behavioral and neuroanatomical changes were restored in DISC1 mice after doxycycline treatment to shut down expression of mutant DISC1, indicating that expression of this risk factor was necessary for adolescent cannabis to produce the clinical manifestations in adulthood. Our studies suggest that both shared and cell type specific alterations could explain variable phenotypic manifestations of gene-environment interactions consistent with symptom heterogeneity of psychotic disorders [4].
References [1] Abazyan B, Nomura J, Kannan G, Ishizuka K, Tamashiro KL, Nucifora F, Pogorelov V, Ladenheim B, Yang C, Krasnova IN, Cadet JL, Pardo C, Mori S, Kamiya A, Vogel MW, Sawa A, Ross CA, Pletnikov MV. Prenatal interaction of mutant DISC1 and immune activation produces adult psychopathology. Biol Psychiatry. 2010 Dec 15; 68(12): 1172−81. [2] Abazyan B, Dziedzic J, Hua K, Abazyan S, Yang C, Mori S, Pletnikov MV, Guilarte TR. Chronic exposure of mutant DISC1 mice to lead produces sex-dependent abnormalities consistent with schizophrenia and related mental disorders: a gene-environment interaction study. Schizophr Bull. 2014 May; 40(3): 575−84. [3] Ballinger MD, Saito A, Abazyan B, Taniguchi Y, Huang CH, Ito K, Zhu X, Segal H, Jaaro-Peled H, Sawa A, Mackie K, Pletnikov MV, Kamiya A. Adolescent cannabis exposure interacts with mutant DISC1 to produce impaired adult emotional memory. Neurobiol Dis. 2015 Oct; 82: 176−84. [4] Ayhan Y, McFarland R, Pletnikov MV. Animal models of geneenvironment interaction in schizophrenia: A dimensional perspective. Prog Neurobiol. 2016 Jan; 136: 1−27.
S.33. Phenotype-genotype interactions in developmental disorders S.33.02 Is it possible to reduce phenotypic heterogeneity in a biological meaningful way? A.M. Persico1 ° 1 University of Messina, Child and Adolescent Neuropsychiatry, Messina, Italy The biological components of pathogenetic processes leading to psychopathology are far less numerous than its many triggers, as these converge downstream upon a relatively limited number of mechanisms and pathways, whether be causal or predisposing. A paradigmatic examples is represented by Autism Spectrum Disorder (ASD), a heterogeneous and severe disorder with onset during early childhood and typically a life-time persistent course. The majority of ASD cases stems from complex, “multiplehit”, oligogenic/polygenic contributions involving several loci, together with variable gene-environment interactions and immune abnormalities. These multiple layers of complexity require diagnostic and prognostic biomarker sets collecting information from multiple levels of an individual’s biology, ranging from basic genetics to cognitive processing [1]. Within this framework, unbiased metabolomic analysis offers a sensitive tool to search for urinary metabolite profiles potentially usable as biomarkers for neurodevelopmental disorders. Young ASD children (N = 30, age 2−7) significantly differ from matched controls especially in tryptophan and purine metabolic pathways [2], largely overlapping with results found in rodent models of ASD following maternal immune activation or genetic manipulations [3]. These metabolic abnormalities could underlie several comorbidities frequently associated with ASD, such as seizures, sleep disorders, and gastrointestinal symptoms, and could contribute to autism severity. The potential association between urinary metabolomic patterns, clinical comorbidities and behavioral abnormalities is being investigated. Merging of this information with genetic, electrophysiological and brain imaging data is predicted to maximize validity and predictive power. References [1] Ruggeri B, Sarkans U, Schumann G, Persico AM. Biomarkers in autism spectrum disorder: the old and the new. Psychopharmacology (Berl) 2014; 231:1001–1016.