Matthew P. Lungren Michael R.B. Evans Editors TreatmentClinical Medicine Resistance inCove Psychiatryrtemplate RiskSubtitle Factors, for Biology, and ManagementClinical Medicine Covers T3_HB Yong-KuSecond Ed Kimition Editor 123123 Treatment Resistance in Psychiatry Yong-Ku Kim Editor Treatment Resistance in Psychiatry Risk Factors, Biology, and Management Editor Yong-Ku Kim Department of Psychiatry College of Medicine, Korea University Seoul South Korea ISBN 978-981-10-4357-4 ISBN 978-981-10-4358-1 (eBook) https://doi.org/10.1007/978-981-10-4358-1 Library of Congress Control Number: 2018957846 © Springer Nature Singapore Pte Ltd. 2019 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd. The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721, Singapore Preface Despite its great progress in psychopharmacology, a significant proportion of psychiatric patients do not respond satisfactory to the treatment. Given the lack of consistence for defining criteria, it is difficult to assess the accurate prevalence of treatment-resistant psychiatric disorders. Approximately 30% of psychiatric patients would be considered recovered from the standard treatments, 30–40% of patients would be considered improved, whereas 30% of patients would be barely touched by the contemporary treatments. In spite of the fact that there is no full agreement regarding the definition of treatment resistance of psychiatric disorders, treatment resistance clearly refers to the occurrence of an inadequate response following adequate treatment. Coping with the treatment resistance in psychiatric disorders is an important issue facing psychiatrists and their patients. The search of potential biological markers for treatment-resistant psychi- atric disorders is a current challenge in the field of biological psychiatry. One way to fulfill these challenges would be to investigate molecular and cellular causes responsible for the treatment resistance using blood and cerebrospinal fluid analysis, neuroimaging, and genetic and epigenetic techniques. Then, obtained biological markers would be used for developing clinical risk fac- tors for treatment resistance and for delivering effective treatments to reach complete remission of symptoms. However, the goal is presently out of reach. Therefore, we need to think outside the box and get away from conventional ways of thinking. Post hoc experimental design can be regarded only as a consequence of having treatment-resistance, rather than being causal risk factors for it. So, we need a paradigm shift toward cause-and-effect relationship. Our lack of information on treatment resistance can start with the misinterpreted post hoc design of many studies. To deal with this situation, untreated patients are enrolled in the study to identify biological markers for treatment resistance. This book reviews all the important aspects of treatment-resistant psychi- atric disorders, covering issues such as definitions, clinical aspects, neurobio- logical correlates, treatment options, and predictors of treatment response. The book is divided into three parts, the first (Chaps. 1, 2, 3, 4, 5, and 6) of which examines the most recent thinking on treatment resistance in psychia- try, including definition and epidemiology, paradigm shift in the study of the subjects, individual susceptibility and resilience, abnormal structural or func- tional connectivity, and insights from animal models. The second (Chaps. 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, and 18) part then discusses treatment v vi Preface resistance in each of the major psychiatric disorders, with particular focus on the responsible clinical and biological factors and the available management strategies. Finally, in third (Chaps. 19, 20, 21, 22, 23, 24, and 25) part, more detailed information is presented on diverse pharmacological and nonphar- macological therapeutic interventions. The book, written by leading experts from across the world, will be of value to all who seek a better understanding of the clinical-neurobiological underpinnings and the development of man- agement for treatment resistance in psychiatric disorders. Chapter 1 highlights a current and available knowledge about definition, epidemiology, risk factors, and improving strategies of treatment resistance in mental disorders. The definition of treatment resistance in psychiatry remains controversial in spite of importance. Most definitions have focused on pharmacotherapy but even these have struggled to capture the complexity of varying response and duration of treatment. This review discusses the importance of treatment resistance and factors affecting its definition in the light of recent advances in knowledge and treatment. The optimization of treatment, such as personalized medicine, measurement-based care, combi- nation and augmentation strategies and experimental treatment strategies, diminishes the occurrence of treatment resistance. Chapter 2 reviews some methodological considerations to uncover initial risk factors for treatment-resistant psychiatric disorders and propose a better study design for future research by discussing the shortcomings of traditional study design. The post hoc experimental design can be regarded only as a consequence of having treatment resistance, rather than being causal risk fac- tors for it. Data derived from such studies often do not allow for a distinction to be made between cause and effect. To deal with this problem, untreated patients should be enrolled in the study to identify biological markers for treatment resistance. Such information can give a cue to improve the initial diagnosis and provide more effective treatment for treatment resistance. Chapter 3 focuses on clinical evidences from pharmacogenetic or pharma- cogenomic data in major psychiatric disorders in order to better understand potential biomarkers that can be aid in the prediction of therapeutic response. Although the search for genetic biomarkers is facilitated by several approaches including epidemiological studies, molecular methods, genome-wide associ- ation studies, transcriptional and microRNA analyses, gene-environment interaction, and epigenetic approaches, no biomarkers have good enough sen- sitivity and specificity to be applied in clinical practice at present. The major- ity of available pharmacogenetic studies in psychiatry refers to how a specific gene or a set of genes can influence a patient’s response or side effects and only few of them are specifically designed to explore biomarkers underlying treatment resistance. Chapter 4 illustrates recent study findings regarding clinical application of brain-based biomarkers derived from patients for the prediction of response or resistance to treatment, as well as for improved design of clinical studies, to find more robust brain-based biomarkers of treatment response or resis- tance. Earlier identification of patients who are prone to treatment resistance can avoid the frustration of a trial-and-error approach and facilitate the design of more optimized treatment regimens and setting of individualized levels of Preface vii care. In future, more active application of machine-learning and medical bio- informatics frameworks to the brain biomarker-based prediction of treatment response and recommendation of a personalized treatment regimen are warranted. Chapter 5 suggests ways to develop new drugs that may be effective in the treatment of resistant depression. Animal models of depression have been developed with a focus on those likely to demonstrate useful drugs in resis- tant depression or associations. Are there animal models for resistant depres- sion? Researchers have proposed models likely to develop drugs that can treat resistant depression. A potential model to discover antidepressants active in resistant depression is based on genetic. To date, the genetic model has not been used in the development of treatments for resistant depression, but it is a path that seems interesting. Chapter 6 highlights the hypothetical conceptualization of an integrated approach to treatment-resistant psychiatric disorders. The integrated approaches for treatment-resistant psychiatric disorders can be an important issue in the perspective of clinical psychiatry. The synergistic