Personalized psychiatry:
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| Beschreibung: | xxv, 566 Seiten Illustrationen, Diagramme |
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| adam_text | Contents Contributors Preface xvii XXV 1. What is personalized psychiatry and why is it necessary? Bernhard T Baune 2. The modeling of trajectories in psychotic illness Scott R. Clark, Klaus Oliver Schubert and Bernhard T. Baune 1. Introduction 2. Sample trajectories (between-subject analyses) 2.1 Simple Bayesian trajectories 3. Subgroup and individual trajectories (between- and within-subject analyses) 3.1 Mixed modeling 3.2 Structural equation modeling 4. Discussion 4.1 Future designs in trajectory research 4.2 Conclusions References 3 4 6 6 7 8 9 10 10 10 3. Mood trajectories as a basis for personalized psychiatry in young people Klaus Oliver Schubert, Scott R. Clark, Linh K. Van, Jane L Collinson and Bernhard T Baune 1. Introduction 2. Three types of studies investigate depressive symptom trajectories in young people 3. The shape and the number of depressive symptom trajectories in young people 3.1 The shape of depressive symptom trajectories in young people 13 13 14 15 3.2 The number of depressive symptom trajectories in young people 4. Risk factors for specific mood symptom trajectory membership 4.1 Gender 4.2 Physical developmental factors 4.3 Parental history of mental disorders and other parental factors 4.4 Interpersonal relationship factors 4.5 Physical health factors 4.6 Socioeconomic factors 4.7 Psychosocial stressors in childhood 4.8 Ethnic factors 4.9 Psychological factors 4.10 Lifestyle factors 5. The contribution of specific and predefined risk factors to depressive symptom trajectories 5.1 Gender 5.2 Ethnicity and minority group membership 5.3 Physical
health 5.4 Genetic factors 5.5 Psychological factors 6. Concurrent trajectories of depressive symptoms and other longitudinally measured factors 6.1 Concurrent trajectories of mood symptoms and trauma/life events/stress 6.2 Concurrent trajectories of mood and delinquency/oppositional defiance 6.3 Concurrent trajectories of depressive symptoms and body mass index 6.4 Concurrent trajectories of depressive symptoms and substance use 7. Summary of findings on depressive symptom trajectories in young people 8. Implications for clinical practice and research 9. Limitations 10. Conclusions References Further reading 15 16 16 16 17 17 17 17 17 17 17 17 18 18 18 19 19 19 20 20 20 20 21 21 23 24 24 24 26 V
vi Contents 4. Transdiagnostic early intervention, prevention, and prediction in psychiatry Cristina Mei, Barnaby Nelson, Jessica Hartmann, Rachael Spooner and Patrick D. McGorry 1. Introduction 2. Emergence and progression of mental disorders 3. Transdiagnostic approaches to diagnosis and classification 3.1 Clinical staging 4. Prediction of mental disorder onset and progression 4.1 Dynamic prediction techniques 5. Transdiagnostic early intervention and clinical services 5.1 Transdiagnostic, stage-based care 5.2 Applying a transdiagnostic clinical staging model within youth mental health services 6. Conclusion References 27 27 28 28 29 30 31 33 33 34 34 5. Early intervention, prevention, and prediction in mood disorders: Tracking multidimensional outcomes in young people presenting for mental health care Elizabeth M. Scott, Joanne S. Carpenter, Frank lorfino, Shane P.M. Cross, Daniel F. Hermens, Django White, Rico S.Z. Lee, Sharon L. NaismithՆ Adam J. Guastella, Nicholas dozier, F. Markus Leweke, Dagmar Koethe, Jim Lagopoulos, Jan Scott, Blake A. Hamilton, Jacob J. Crouse, Ashleigh M. Tickell, Alissa Nichles, Natalia Zmicerevska, Lillian J. Gehue, Manreena Kaur, Kate M. Chitty and Ian B. Hickie 1. Developing an early intervention mood disorders service 2. Characteristics of the Brain and Mind Center youth cohort 3. Data collection process 4. Demographic, symptom, and social and occupational functioning of the brain and mind youth mood disorders cohort 5. Developing a multidimensional outcome framework for young people with emerging mood disorders 39 42 43 43 43 6. Illness
type, clinical stage, and lifetime trajectory 6.1 Illness type 6.2 Clinical stage 6.3 Lifetime trajectory 7. Testing the robustness and clinical utility of a multidimensional outcomes framework 8. Designing personalized treatments based on illness type and clinical stage 9. Designing health services to respond to early mood disorders: Opportunities for early intervention and secondary prevention 10. Testing novel treatments 11. Conclusions References 44 1 462 53 46 47 47 55 56 56 56 57 6. Consumer participation in personalized psychiatry Harris A. Eyre, Elisabeth R.B. Becker, Marissa S. Blumenthal, Ajeet B. Singh, Cyrus Raji, Arshya Vahabzadeh, Zoe Wainer and Chad Bousman 1. Introduction 2. Consumer participation in research 2.1 Sociodemographic considerations 2.2 Citizen science as a model 2.3 Patient-Centered Outcomes Research Institute (PCORI) 2.4 Precision Medicine Initiative 2.5 Online patient communities as clinical and research tools 3. Consumer participation in novel solution development 4. Consumer participation in clinical care 4.1 Shared decision making (SDM) 5. Consumer participation in policy 5.1 Reimbursement 6. Discussion 6.1 Future roles of online patient communities as clinical and research tools 6.2 Future roles of design thinking in novel solution development and shared decision making in clinical care 7. Conclusion References 63 63 64 64 64 64 64 65 65 65 66 66 66 67 67 67 67
Contents Experimental validation of psychopathology in personalized psychiatry Alfons О. Hamm 1. Introduction 2. Psychopathology of anxiety disorders 2.1 Experimental validation of fear and anxiety 2.2 Empirical evaluation of the model in humans 3. Neural network activation 4. Avoidance behavior as an index of functional impairment 5. Clinical implications: Anxiety disorders 5.1 Toward personalized treatment: Genetic and behavioral data References Further reading 69 69 70 72 75 10. Statistical genetic concepts in psychiatric genomics 77 77 Darina Czamara and Divya Mehta 79 79 82 8. Deep brain stimulation for major depression: A prototype of a personalized treatment in psychiatry Thomas E. Schlaepfcr and Bettina H. Bewernlck 1. The need for personalized treatment in psychiatry 2. Deep brain stimulation 2.1 Targets for depression 2.2 Antidepressant efficacy 2.3 DBS for treatment-resistant depression— State of the art 2.4 Stimulating with high spatial precision 2.5 From stimulating targets to modulating networks 2.6 Relating clinical symptom clusters to dysfunctional brain networks 2.7 Is there a target—Specific effect for subtypes of depression? 3. Current research strategies for the individualized treatment of depression 4. Summary and outlook References 83 83 84 84 84 1. Genetic studies 1.1 Genetic linkage studies 1.2 Genetic association studies 1.3 Genome-wide association studies 1.4 CNV analysis 1.5 Family-based association studies 1.6 Twin studies 2. Genetic architecture 2.1 Population stratification 2.2 Imputation of missing genotypes 2.3 Heritability, genetic
correlation, and polygenic risk scores 3. Gene-environment interactions 4. Gene expression and DNA méthylation analysis 5. Gene enrichment and network analysis 6. Conclusions and future directions References Further reading 92 92 92 92 93 97 98 99 103 103 104 104 105 105 106 106 106 106 106 107 109 110 110 111 116 85 86 86 86 87 87 9. The Psychiatric Genomics Consortium: History, development, and the future Hunna I. Watson, Zeynep Yilmaz and Patrick F. Sullivan 1. Background 1.1 Heritability in psychiatric disorders 1.2 Linkage and candidate gene studies 1.3 Polygenicity 1.4 High-throughput assays 2. History, development, and contributions of the Psychiatric Genomics Consortium 2.1 History and aims 2.2 Contributions 3. What does the future hold? 4. Conclusions References vii 91 91 91 11. Opportunities and challenges of machine learning approaches for biomarker signature identification in psychiatry Han Cao and Emanuel Schwarz 1. Introduction 2. Opportunities 2.1 Knowledge incorporation via regularization 2.2 Knowledge incorporation via Bayesian methods 2.3 Knowledge incorporation via Kernel methods 3. Challenges 3.1 Imputation approaches based on correlation structure 3.2 Imputation approach based on additional knowledge 4. Conclusion 117 118 118 120 121 122 122 123 123
Contents Acknowledgment References Further reading 124 124 126 12. Personalized psychiatry with human iPSCs and neuronal reprogramming Cedric Bardy, Zarina Greenberg, Seth W. Perry and Julio Licinio 1. Introduction 1.1 Psychiatry needs precision medicine 1.2 Limitations of existing (non-iPSC) models 2. iPSC-derived neurons for personalized psychiatry: Opportunities and challenges 2.1 Genetics, epigenetics, and iPSCs in psychiatric disease 2.2 Applying iPSCs to personalized psychiatry 2.3 Challenges for optimal use of neuronal reprogramming in personalized psychiatry 3. Using iPSCs for psychiatric disease modeling 3.1 iPSCs in bipolar disorder 3.2 iPSCs in depression and anxiety disorders 3.3 iPSCs in schizophrenia 3.4 iPSCs in autism spectrum disorder 4. Conclusions and future directions References Further reading 127 127 128 128 128 131 133 135 135 137 138 138 139 139 146 Jill L. Sorcher and Falk W. Lohoff 147 151 151 151 152 154 155 155 155 14. Genomics of autism spectrum disorders Margarita Raygada, Paul Grant and Owen M. Rennert 1. Definition of the clinical phenotype 1.1 Background and emerging diagnosis 1.2 Incidence 162 162 162 162 163 164 166 167 167 168 168 169 171 15. Genomics of schizophrenia A. Corvin, C. Ormond and A.M. Cole Genetics of alcohol use disorder 1. Introduction 2. Twin studies 3. Linkage studies 3.1 Candidate gene association studies 3.2 Genome-wide association studies 3.3 GCTA/GREML methods 3.4 Whole genome sequencing 4. Conclusions References 1.3 Cost of autism spectrum disorders 1.4 Current state of personalized care 2. Genetic causes of autism
spectrum disorders 2.1 Syndromic ASD 2.2 Nonsyndromic 3. Diagnostic work-up for nonsyndromic autism spectrum disorders 4. Pathway analysis and molecular networks 5. Genetic counseling of autism spectrum disorders 5.1 Navigating the diagnostic work-up 5.2 Managing the patient and helping the family cope 6. Summary References Further reading 161 161 161 1. Introduction 2. Schizophrenia heritability 3. An emerging genetic architecture of schizophrenia 4. Genome-wide association studies 5. Rare structural risk variants 6. Genome-sequencing studies 7. From gene discovery to etiology 8. Genetic architecture 9. Diagnostics 10. Localizing risk genes 11. Molecular mechanisms and pathways 12. Drug discovery 13. Personalized treatment 14. Conclusion References 173 173 174 174 175 176 178 178 179 180 180 181 182 182 183 16. Genomics of major depressive disorder Douglas F. Levinson 1. What is the phenotype? 2. Genetic epidemiology 3. Do proband characteristics predict familial risk? 4. Relationship of MDD to bipolar disorder and schizophrenia: Epidemiology 5. Childhood trauma and other stressful events 6. Molecular genetic methods 7. G WAS of depression 7.1 Large-scale GWAS analyses 187 187 188 188 188 188 189 189
Contents 7.2 What can we learn from the results so far? 7.3 Common-SNP heritability and genetic correlations among datasets 7.4 Genetic pathway findings 7.5 Single-locus associations 7.6 Genetic correlation with psychiatric and nonpsychiatric traits 8. Large-scale studies of gene expression 9. Studies of candidate genes and polymorphisms 9.1 5-HTTLPR genotype and the risk of depressive episodes following stress 10. Pharmacogenomic prediction of antidepressant medication response 11. Conclusions and future directions Disclosure Statement References 191 191 192 192 194 194 195 195 196 197 197 197 17. Personalized mental health: Artificial intelligence technologies for treatment response prediction in anxiety disorders 201 201 201 202 204 204 208 208 208 209 209 210 211 Olav В. Smeland, Andreeis J. Forstner, Alexander Charney, EU A. Stahl and Ole A. Andreassen 1. 2. 3. 4. Introduction Family studies Twin and adoption studies Molecular genetics 215 215 215 216 4.1 Linkage studies 4.2 Association studies 216 216 217 217 217 7.1 Recent G WAS of B D 218 7.2 Genetic overlap 218 7.3 Novel polygenic analytical approaches 220 8. From genetic loci to disease mechanisms 9. Contribution of rare variants 10. Clinical implications of genetic knowledge 11. Conclusion Acknowledgments Competing Financial Interests References 204 204 205 207 209 18. The genetic architecture of bipolar disorder: Entering the road of discoveries 5. Genome-wide association studies 6. GWASinBD 7. Genetic architecture of BD Ulrike Lueken and Tim Hahn 1. Introduction 1.1 Interindividual variability in normal to
pathological forms of fear and anxiety 1.2 What is a predictive biomarker? 1.3 Targeting nonrespondent patients by personalizing treatments? 1.4 Novel methods for mental health predictomics 1.5 Aims and contents of this chapter 2. Neurobiological markers of treatment response: Available evidence 2.1 (Epi)genetic markers 2.2 Neuroimaging markers 2.3 Single-case predictions 3. Toward personalized clinical decision support systems: Current status quo and future challenges 3.1 Model construction and validation: The relevance of real-life, heterogeneous patient samples 3.2 Novel approaches and technologies provided by machine learning and artificial intelligence 3.3 Sharing pretrained models rather than original data 3.4 Legal issues, data privacy, security, and ownership associated with predictive analytics 3.5 Turning robust, validated biomarker models into clinical decision support systems 4. Conclusionsand outlook References ίχ 221 221 222 222 223 223 223 19. Genomics of borderline personality disorder Fabian Streit, Lucía Colodro-Conde, Alisha S.M. Hall and Stephanie H. Witt 1. Clinical aspects of borderline personality disorder 2. Genetic studies 2.1 Formal genetic studies 2.2 Molecular genetic studies 2.3 Epigenetic factors 3. Summary 4. Future directions References 227 228 228 229 232 233 233 234
x Contents 20. Genetics of obsessive-compulsive disorder and Tourette disorder 22. Genomics of Alzheimer s disease Margot P. van de Weijer, Iris E. Jansen, Anouk H.A. Verboven, Ole A. Andreassen and Danielle Posthuma Christie L. Burton, Csaba Barta, Danielle Cath, Daniel Geller, Odile A. van den Heuvel, Yin Yao, (Obsessive Compulsive Disorder and Tourette Syndrome Working Group of the Psychiatric Genomics Consortium), Valsamma Eapen, Edna Grünblatt and Gwyneth Zai 1. Introduction 1.1 Heritability and familiality of OCD and TD 1.2 Candidate gene studies in OCD and TD 1.3 Genome-wide association studies in OCD and TD 1.4 Copy number variation in OCD and TD 1.5 Whole exorne sequencing in OCD and TD 1.6 Pharmacogenetics of antidepressants in OCD and TD 1.7 Imaging genetics of OCDand TD 1.8 Epigenetics of OCD and TD 1.9 Gene x environment of OCD and TD 2. Conclusion and future perspective Acknowledgments References 239 239 240 240 242 243 243 244 245 246 246 246 246 21. Genetics and pharmacogenetics of attention deficit hyperactivity disorder in childhood and adulthood Cristian Bonvicini, Carlo Maj and Catia Scassellati 1. Introduction 1.1 Genetics: Stateof the art 1.2 Pharmacogenetics:State of the art 2. Role of SLC6A3 gene as a potential genetic biomarker in ADHD diagnosis in children and adults 2.1 Methods 2.2 Results 3. Role of SLC6A3 gene as potential mediator/predictor of the MPH drug response in children and inadults 3.1 Methods 3.2 Results 4. Discussion and futureresearch 5. Conclusion References 253 254 255 256 256 262 1. Introduction 2. The genetics ofAD 3. Other
omicsapproaches 4. Conclusion References 275 277 280 282 282 23. Current progress and future direction in the genetics of PTSD: Focus on the development and contributions of the PGC-PTSD working group Angela G. Junglen, Christina Sheerin, Douglas L. Delahanty, Michael A. Hauser, Adriana Lori, Rajendra A. Morey, Caroline M. Nievergelt, Nicole R. Nugent, Jonathan Sebat, Alicia K. Smith, Jennifer A. Sumner, Monica Uddin and Ananda В. Amstadter 1. Introduction 2. Behavioral genetics of PTSD 3. Molecular genetic studies 3.1 Candidate gene studies 3.2 cGxE studies 3.3 Genome-wide association studies 4. Psychiatric Genomics Consortium 5. Initial findings from the PGC-PTSD 6. Unique considerations of the PGC-PTSD 7. Development of the PGC-PTSD working groups 7.1 Gene expression working group 7.2 EWAS working group 7.3 Neuro-imaging working group 7.4 Physical health working group 7.5 CNV working group 8. Future directions of the PGC-PTSD and PTSD genomics as a whole References 285 286 286 286 286 287 287 289 289 290 290 290 291 291 292 292 293 24. Genomic contributions to anxiety disorders Shareefa Dalvie, Nastassja Koen and Dan J. Stein 262 262 264 264 269 270 1. 2. 3. 4. 5. 6. Introduction Family and twin studies Linkage studies Candidate gene association studies Genome-wide association studies Post-GWAS analysis 297 297 298 298 298 301
Contents 7. Expression analysis 8. Epigenetics 9. Next-generation sequencing 10. Copy number variation 11. Pharmacogenomics 12. Future directions 13. Conclusions References 301 302 302 302 302 303 303 303 25. Proteomics for diagnostic and therapeutic blood biomarker discovery in schizophrenia and other psychotic disorders 307 307 308 308 308 309 310 310 310 311 311 314 315 26. Molecular biomarkers in depression: Toward personalized psychiatric treatment Anand Gururajan, John F Cryan and Timothy G Dinan 1. Personalized psychiatry—A pipedream or a possibility? 1.1 Challenges in diagnosis 1.2 A role for biomarkers? 2. Noncoding RNAs 2.1 MicroRNAs 2.2 Long noncoding RNAs 2.3 Perspective 3. Coding transcriptomic and proteomic biomarkers 3.1 Neurotransmitters 3.2 BDNF and growth factors 327 328 329 329 329 329 329 331 332 338 27. Neuroimaging biomarkers of late-life major depressive disorder pathophysiology, pathogenesis, and treatment response David R. Cotter, Sophie Sabherwal and Klaus Oliver Schubert 1. Proteomics for complex psychiatric disorders 2. Proteomics and personalized psychiatry 3. Mass spectrometry workflows 4. Mass spectrometry subtypes 5. Acquisition methods for proteomic data 6. Multiplex immunoassays 7. A comparison between mass spectrometry and multiplex immunoassay 8. Data analysis and bioinformatics 9. Functional analysis of proteomic data 10. Proteomics for blood biomarker discovery in psychiatry 10.1 The search for schizophrenia biomarkers: An example of psychiatric biomarker discovery 11. Conclusion References 3.3 Biomarkers associated with the HPA axis
3.4 Inflammatory biomarkers 3.5 Perspective 4. Genomic biomarkers 4.1 Mitochondrial DNA 4.2 Telomeric biomarkers 5. The gut microbiome 6. Concluding remarks References Further Reading x¡ 319 319 320 320 320 321 322 322 322 324 Helmet T. Karim, Charles F. Reynolds, III and Stephen F. Smagula 1. Neuroimaging biomarkers of LLD pathophysiology 1.1 Section summary 1.2 White matter biomarkers 1.3 Gray matter biomarkers 1.4 Functional activation biomarkers 1.5 Functional connectivity biomarkers 1.6 Cerebral blood flow biomarkers 2. Neuroimaging biomarkers of LLD pathogenesis 2.1 Section summary 2.2 White matter integrity and depression development 2.3 Regional brain volume and depression development 3. Neuroimaging biomarkers of LLD treatment response 3.1 Section summary 3.2 White matter integrity and treatment response 3.3 Regional brain volume and treatment response 3.4 Functional activation and treatment response 3.5 Functional connectivity and treatment response 3.6 Cerebral blood flow and treatment response 4. Machine learning to predict LLD and treatment response 5. Conclusion and future directions Acknowledgments References 340 340 341 341 342 342 343 344 344 344 344 344 344 344 345 345 346 346 346 347 351 351
xii Contents 28. Copy number variants in psychiatric disorders 7. Upregulation of BDNF signaling and antidepressant treatment response to ECT 8. Conclusion and outlook References Franziska Degenhardt 1. Copy number variation and the human genome 2. Identification of copy number variants 3. Copy number variants and study designs 4. Copy number variants and clinical translation efforts 5. Concluding remarks and future perspectives Conflict of interest References 358 358 359 359 360 360 360 29. Gene-environment interaction in psychiatry Hans Jörgen Grabe and Sandra Van der Auwera 1. 2. 3. 4. 5. Introduction Environmental conditions Candidate genes Depressive disorders and anxiety The insertion/deletion polymorphism of the serotonin transporter gene (5-HTTLPR) 6. FKBP5 gene 7. Brain-derived neurotrophic factor (BDNF) 8. Genome-wide challenges of GxE 9. Schizophrenia and bipolar disorder 10. Future relevance of GxE interaction References 363 363 364 365 365 366 366 367 367 368 369 30. Epigenetics: A new approach to understanding mechanisms in depression and to predict antidepressant treatment response Helge Frieling, Stefan Bleich and Alexandra Neyazi 1. The main epigenetic processes that may be used as biomarkers for treatment response are DNA modifications, noncoding RNAs, and histone modifications 376 2. DNA méthylation, stress,and depression 377 3. Brain-derived neurotrophic factor and depression 377 4. Méthylation patterns as biomarkers for depression 378 5. BDNF méthylation and antidepressant response 378 6. BDNF modifications and response to ECT 379 379 380 380 31. Gene
coexpression network and machine learning in personalized psychiatry Liliana G. Gobanu, Micah Cearns and Bernhard T Baune 1. Introduction 2. Diagnosis 2.1 Coexpression network analysis to differentiate disease from healthy controls 2.2 Weighted gene coexpression network analysis 2.3 Differential coexpression network analysis to study differences among gene interconnections 3. Diagnosis of patient subtypes 3.1 Biclustering for identifying subgroups of patients 4. Personalized treatment 4.1 Gene coexpression networks for understanding treatment response biotypes 5. Disease mechanisms 5.1 Gene coexpression network for integrative analyses in psychiatry 5.2 Shared molecular mechanisms among disorders: Implications for treatment response 6. Future methods: Machine learning 6.1 Gene selection and complex trait prediction 6.2 Applications for gene expression Conclusions References 385 386 386 386 387 387 387 387 387 388 388 388 388 389 389 390 390 32. Pharmacogenomics of bipolar disorder Claudia Pisanu, Alessio Squassina, Martin Alda and Giovanni Severino 1. Genetic bases of BD 2. Clinical heterogeneity of BD and pharmacological treatments 3. Pharmacogenetics of lithium: Candidate genes studies 3.1 Neurotransmittersystems 393 393 394 394
Contents xiii 3.2 Neurothrophic factors 3.3 Inositol signaling pathway 3.4 GSK-3 and circadian clock rhythms 4. Pharmacogenetics of lithium: Genome-wide association studies 5. Pharmacogenetics of other mood stabilizers 6. Pharmacogenetics of mood stabilizers: Focus on side effects 7. Conclusions and future perspective References Further Reading 395 396 396 397 397 398 398 399 402 Estela Salagre, Eduard Vieta and tria Grande Joanna M. Biernacka, Ahmed T Ahmed, Balwinder Singh and Mark A. Frye 403 404 404 405 405 407 1. Introduction 2. Tools for personalized treatment in BD 2.1 Clinical and psychobiographical features 2.2 Biological variables 2.3 Technology and personalized psychiatry 3. Ethical issues in personalized psychiatry 4. Summary and futuredirections References 423 423 424 425 428 429 429 431 36. Genetic testing in psychiatry: State of the evidence Chad A. Bousman, Lisa C. Brown, Ajeet B. Singh, Harris A. Eyre and Daniel J. Miiller 408 408 408 409 410 410 34. Genomic treatment response prediction in schizophrenia Sophie E. Legge, Antonio F. Pardiñas and James T.R. Walters 1. Introduction 1.1 Burden of 1RS 1.2 Clozapine treatment 414 414 414 415 416 417 417 418 418 419 419 35. Personalized treatment in bipolar disorder 33. Pharmacogenomics of treatment response in major depressive disorder 1. Introduction 2. Candidate gene pharmacogenetic studies of antidepressant response 2.1 Pharmacokinetic candidate genes 2.2 Pharmacodynamic candidate genes 3. GWAS of antidepressant response 4. Antidepressant pharmacogenomics study design and definition of treatment outcomes:
Impact on research findings and clinical relevance 5. Novel approaches to identifying pharmacogenomic effects and their application in studies of antidepressant response 6. Antidepressant pharmacogenomics resources 7. The emergence of pharmacogenomic tests to individualize treatment of MDD 8. Future considerations 9. Conclusion References 2. Prediction of TRS 3. Genomic prediction of TRS 3.1 Heritability of TRS 3.2 Candidate studies 3.3 GWAS 3.4 Genetic liability to schizophrenia 3.5 Rare variant studies 4. Glutamate hypothesis of TRS 5. Challenges and future directions 6. Conclusions References 413 413 413 1. Introduction 2. Types of genetic tests 3. Current evidence base 3.1 Genetic tests for identifying at risk individuals 3.2 Genetic tests for assisting with diagnosis 3.3 Genetic tests to guide optimal therapy 4. Strategies for strengthening the evidence base 4.1 Phenotype definition and measurement 4.2 Pharmacogenetic testing panel and reporting standardization 4.3 Innovative clinical trials 5. Conclusion References 437 437 438 438 438 439 442 442 444 444 445 445
xiv Contents 37. Opportunities and challenges of implementation models of pharmacogenomics in clinical practice 39. Real-time fMRI brain-computer interface: A tool for personalized psychiatry? David E.J. Linden Jonathan C.W. Liu, Ilona Gorbovskaya, Chad Bousman, Lisa C. Brown and Daniel J. Muller 1. Introduction 2. Barriers to implementing pharmacogenetic tests 2.1 Access to laboratory and analytical validity 2.2 Establishing genotyping 2.3 Cost effectiveness 2.4 Ethical considerations 2.5 Providers, payers, and industry perspectives 3. Education and opportunities to implement pharmacogenetic tests 3.1 Education—Patients 3.2 Education—Physicians 3.3 Education—Nurses 3.4 Education—Pharmacists 4. Pharmacogenetic testing s role in collaborative care and shared decision making 5. The IMPACT study at the Centre for Addiction and Mental Health inToronto 6. Conclusion References Further reading 449 449 449 450 451 451 1. 2. 3. 4. Introduction Principles and methods Clinical applications of fMRI-NF A personalized approach 4.1 Personalized neural targets 4.2 Personalized stimuli and other elements of the neurofeedback therapy 5. Concluding remarks Acknowledgment References 465 466 466 467 467 468 468 468 469 452 452 453 453 453 453 453 454 454 455 457 40. How functional neuroimaging can be used for prediction and evaluation in psychiatry Beata R. Godlewska and Catherine J. Harmer 1. Understanding the neural basis of mental health conditions 2. Identification of individuals at high risk of developing a psychiatric condition 3. Differential diagnosis 4. Treatment choice and
mechanisms of drug action 5. General remarks References Further reading 472 473 474 475 477 478 481 38. Metabolomics in psychiatry Renee-Marie Ragguett and Roger S. McIntyre 1. Why metabolomics in psychiatry? 2. Application of metabolomics in psychiatry 2.1 Disease diagnosis 2.2 Treatment response 2.3 Disease monitoring 3. Limitations of metabolomics in psychiatry 3.1 Environmental variations 3.2 Unknown metabolites 3.3 Availability and application of metabolomic assays in clinic 4. Future vistas 4.1 The human metabolome project 4.2 Integration of other omics 4.3 Personalized medicine References 459 460 460 461 461 462 462 462 462 463 463 463 463 463 41. Neuroimaging, genetics, and personalized psychiatry: Developments and opportunities from the ENIGMA consortium Lianne Schmaal, Christopher R.K. Ching, Agnes B. McMahon, Neda Jahanshad and Paul M. Thompson 1. Introduction 2. Underpowered studies and the crisis of reproducibility 3. The enhancing neuroimaging genetics through meta-analysis consortium 4. ENIGMA imaging genomics and genome-wide association studies 5. ENIGMA psychiatric neuroimaging studies 6. Toward personalized psychiatry 7. Challenges of large-scale data-sharing 483 484 485 487 489 491 492
Contents 8. Conclusions 8.1 Future directions 8.2 Conclusions Acknowledgment References Further reading 493 493 494 494 494 497 511 512 512 512 513 43. Multimodal modeling for personalized psychiatry 42. Applying a neural circuit taxonomy in depression and anxiety for personalized psychiatry Scott R. Clark, Micah Cearns, Klaus Oliver Schubert and Bernhard T. Baune Leanne M. Williams and Andrea N. GoldsteinPiekarski 1. Getting a handle on our terminology for precision psychiatry 2. Foundations for a precision psychiatry taxonomy for depression and anxiety based on neural circuits 3. Default Mode circuit 3.1 Default mode circuit disruptions in depression and anxiety 3.2 Default mode circuit and treatment implications 4. Salience circuit 4.1 Salience circuit disruptions in depression and anxiety 4.2 Salience circuit and treatment implications 5. Affective circuits 6. Negative Affect 6.1 Negative affective circuit disruptions in depression and anxiety 6.2 Negative affective circuit and treatment implications 7. Positive affect circuit: Reward 7.1 Reward circuit disruptions in depression and anxiety 7.2 Reward circuit and treatment implications 8. Attention circuit 8.1 Attention circuit disruptions in depression and anxiety 8.2 Attention circuit and treatment implications 9. Cognitive control circuit 9.1 Cognitive control circuit disruptions in depression and anxiety 9.2 Cognitive control circuit and treatment implications 10. Future directions to close the clinical translational gap 10.1 Standardized protocols 10.2 Normative data 10.3 Integration across modalities within
the same patients 10.4 Computational innovation 10.5 Prospective, circuit-guided interventions 11. Conclusions Acknowledgments References XV 499 500 500 505 505 505 505 506 506 506 507 507 508 508 508 509 509 509 509 510 510 511 511 511 511 1. Introduction 2. Modes of data in psychiatry 2.1 Clinical data 2.2 Cognitive and general function 2.3 Peripheral biomarkers 2.4 Brain imaging and electrophysiology 3. Multivariate modeling 3.1 Study formulation and design 3.2 Model training and testing 3.3 Limitations 3.4 Conclusions and future directions References 521 522 522 523 524 525 525 525 526 530 530 531 44. Standardized biomarker and biobanking requirements for personalized psychiatry Catherine Toben, Victoria K. Arnet, Anita Lo, Pamela H. Saunders and Bernhard T. Baune 1. Personalized psychiatry—from diagnosis to treatment response 2. Fundamentals of biobanking relevant to mental health disorders 2.1 Implementation of a business plan to ensure sustainability 2.2 Regulatory governance 2.3 Sample management and infrastructure for high quality storage of biospecimens 3. Reproducible identification of biomarker signatures within mental health disorders 3.1 Biomarker discovery in psychiatry— considerations, stage I 3.2 Biomarker discovery in psychiatry— considerations stage II 3.3 Biomarker discovery in psychiatry— considerations, stage III 3.4 Future vision for biomarker discovery and validation in psychiatry References 537 537 537 538 540 542 543 544 545 546 546
Contents Ethical, policy, and research considerations for personalized psychiatry Ryan Abbott, Donald D. Chang and Harris A. Eyre Ί. Introduction 2. Ethics 2.1 Big data 2.2 Health disparities 3. Health policy 3.1 Biobanking 3.2 High quality clinical trials 549 549 550 551 551 551 552 3.3 Reimbursement 3.4 Regulation 3.5 Information systemupgrades 4. Medical research 4.1 Research considerations for personalized psychiatry 5. Conclusion References 552 552 553 553 553 554 555 46. The future of personalized psychiatry Bernhard T. Baune Index 559
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| discipline | Psychologie Medizin |
| format | Book |
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| genre | (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV046192763 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T08:37:50Z |
| institution | BVB |
| isbn | 9780128131763 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-031572113 |
| oclc_num | 1136267829 |
| open_access_boolean | |
| owner | DE-11 DE-19 DE-BY-UBM DE-12 DE-473 DE-BY-UBG |
| owner_facet | DE-11 DE-19 DE-BY-UBM DE-12 DE-473 DE-BY-UBG |
| physical | xxv, 566 Seiten Illustrationen, Diagramme |
| publishDate | 2020 |
| publishDateSearch | 2020 |
| publishDateSort | 2020 |
| publisher | Academic Press |
| record_format | marc |
| spelling | Personalized psychiatry edited by Bernhard T. Baune London ; San Diego ; Cambridge ; Oxford Academic Press © 2020 xxv, 566 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Psychiatrie (DE-588)4047667-4 gnd rswk-swf Psycholytische Therapie (DE-588)4121534-5 gnd rswk-swf Personalisierung (DE-588)4384600-2 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Psychiatrie (DE-588)4047667-4 s Psycholytische Therapie (DE-588)4121534-5 s Personalisierung (DE-588)4384600-2 s DE-604 Baune, Bernhard T. 1966- (DE-588)118031481 edt Digitalisierung UB Bamberg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031572113&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Personalized psychiatry Psychiatrie (DE-588)4047667-4 gnd Psycholytische Therapie (DE-588)4121534-5 gnd Personalisierung (DE-588)4384600-2 gnd |
| subject_GND | (DE-588)4047667-4 (DE-588)4121534-5 (DE-588)4384600-2 (DE-588)4143413-4 |
| title | Personalized psychiatry |
| title_auth | Personalized psychiatry |
| title_exact_search | Personalized psychiatry |
| title_full | Personalized psychiatry edited by Bernhard T. Baune |
| title_fullStr | Personalized psychiatry edited by Bernhard T. Baune |
| title_full_unstemmed | Personalized psychiatry edited by Bernhard T. Baune |
| title_short | Personalized psychiatry |
| title_sort | personalized psychiatry |
| topic | Psychiatrie (DE-588)4047667-4 gnd Psycholytische Therapie (DE-588)4121534-5 gnd Personalisierung (DE-588)4384600-2 gnd |
| topic_facet | Psychiatrie Psycholytische Therapie Personalisierung Aufsatzsammlung |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031572113&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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