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A leading goal in the field of biological psychiatry for depression is to find a promising diagnostic biomarker and selection of specific psychiatric treatment mode that is most likely to benefit patients with depression. Recent neuroimaging studies have characterized the pathophysiology of major depressive disorder (MDD) with functional and structural alterations in the neural circuitry involved in emotion or reward processing. Particularly, structural and functional magnetic resonance imaging (MRI) studies have reported that the brain structures deeply involved in emotion regulation or reward processing including the amygdala, prefrontal cortex (PFC), anterior cingulate cortex (ACC), ventral striatum, and hippocampus are key regions that provide useful information about diagnosis and treatment outcome prediction in MDD. For example, it has been consistently reported that elevated activity of the ACC is associated with better antidepressant response in patients with MDD. This chapter will discuss a growing body of evidence that suggests that diagnosis or prediction of outcome for specific treatment can be assisted by a neuroimaging-based biomarker in MDD.

According to the neurotrophic hypothesis of major depressive disorder (MDD), impairment in growth factor signaling might be associated with the pathology of this illness. Current evidence demonstrates that impaired neuroplasticity induced by alterations of neurotrophic growth factors and related signaling pathways may be underlying to the pathophysiology of MDD. Brain-derived neurotrophic factor (BDNF) is the most studied neurotrophic factor involved in the neurobiology of MDD. Nevertheless, developing evidence has implicated other neurotrophic factors, including neurotrophin-3 (NT-3), neurotrophin-4 (NT-4), nerve growth factor (NGF), vascular endothelial growth factor (VEGF), insulin-like growth factor (IGF), glial cell-derived neurotrophic factor (GDNF), and fibroblast growth factor (FGF) in the MDD pathophysiology. Here, we summarize the current literature on the involvement of neurotrophic factors and related signaling pathways in the pathophysiology of MDD.

The Diagnostic and Statistical Manual of Mental Disorder, Fourth Edition (DSM-IV) was revised based on a combination of a categorical and a dimensional approach such that in the DSM, Fifth Edition (DSM-5), depressive disorders have been separated as a distinctive disease entity from bipolar disorders, consistent with the deconstruction of Kraepelinian dualism. Additionally, the diagnostic thresholds of depressive disorders may be reduced due to the addition of "hopelessness" to the subjective descriptors of depressed mood and the removal of the "bereavement exclusion." Manic/hypomanic, psychotic, and anxious symptoms in major depressive disorder (MDD) and other depressive disorders are described using the transdiagnostic specifiers of "with mixed features," "with psychotic features," and "with anxious distress," respectively. Additionally, due to the polythetic and operational characteristics of the DSM-5 diagnostic criteria, the heterogeneity of MDD is inevitable. Thus, 227 different symptom combinations fulfill the DSM-5 diagnostic criteria for MDD. This heterogeneity of MDD is criticized in view of the Wittgensteinian analogy of language game. Depression subtypes determined by disturbances in monoamine levels and the severity of the disease have been identified in the literature. According to a review of the Gottesman and Gould criteria, neuroticism, morning cortisol, cortisol awakening response, asymmetry in frontal cortical activity on electroencephalography (EEG), and probabilistic reward learning, among other variables, are evidenced as endophenotypes for depressive disorders. Network analysis has been proposed as a potential method to compliment the limitations of current diagnostic criteria and to explore the pathways between depressive symptoms, as well as to identify novel and interesting relationships between depressive symptoms. Based on the literature on network analysis in this field, no differences in the centrality index of the DSM and non-DSM symptoms were repeatedly present among patients with MDD. Furthermore, MDD and other depressive syndromes include two of the Research Domain Criteria (RDoC), including the Loss construct within the Negative Valence Systems domains and various Reward constructs within the Positive Valence Systems domain.

Phenotype networks enable clinicians to elucidate the patterns of coexistence and interactions among the clinical symptoms, negative cognitive styles , neurocognitive performance, and environmental factors in major depressive disorder (MDD). Results of phenotype network approach could be used in finding the target symptoms as these are tightly connected or associated with many other phenomena within the phenotype network of MDD specifically when comorbid psychiatric disorder(s) is/are present. Further, by comparing the differential patterns of phenotype networks before and after the treatment, changing or enduring patterns of associations among the clinical phenomena in MDD have been deciphered.Brain structural covariance networks describe the inter-regional co-varying patterns of brain morphologies, and overlapping findings have been reported between the brain structural covariance network and coordinated trajectories of brain development and maturation. Intra-individual brain structural covariance illustrates the degrees of similarities among the different brain regions for how much the values of brain morphological features are deviated from those of healthy controls. Inter-individual brain structural covariance reflects the degrees of concordance among the different brain regions for the inter-individual distribution of brain morphologic values. Estimation of the graph metrics for these brain structural covariance networks uncovers the organizational profile of brain morphological variations in the whole brain and the regional distribution of brain hubs.

Network-based approach for psychological phenotypes assumes the dynamical interactions among the psychiatric symptoms, psychological characteristics, and neurocognitive performances arise, as they coexist, propagate, and inhibit other components within the network of mental phenomena. For differential types of dataset from which the phenotype network is to be estimated, a Gaussian graphical model, an Ising model, a directed acyclic graph, or an intraindividual covariance network could be used. Accordingly, these network-based approaches for anxiety-related psychological phenomena have been helpful in quantitative and pictorial understanding of qualitative dynamics among the diverse psychological phenomena as well as mind-environment interactions. Brain structural covariance refers to the correlative patterns of diverse brain morphological features among differential brain regions comprising the brain, as calculated per participant or across the participants. These covarying patterns of brain morphology partly overlap with longitudinal patterns of brain cortical maturation and also with propagating pattern of brain morphological changes such as cortical thinning and brain volume reduction in patients diagnosed with neurologic or psychiatric disorders along the trajectory of disease progression. Previous studies that used the brain structural covariance network could show neural correlates of specific anxiety disorder such as panic disorder and also elucidate the neural underpinning of anxiety symptom severity in diverse psychiatric and neurologic disorder patients.

Although anxiety and depression have been considered as two distinct entities according to the diagnostic criteria, anxious depression (comorbid anxiety and depression) is relatively a common syndrome. According to the DSM-5 criteria, it uses "with anxious distress specifier" to define anxious depression in its MDD section. Anxious depression is known to have different neurobiological profiles compared to non-anxious depression. Several studies have revealed significant differences between anxious depression and non-anxious depression regarding the hypothalamic-pituitary-adrenal (HPA) axis function, structural and functional brain imaging findings, inflammation markers, etc. Patients with anxious depression were significantly more likely to be found in primary care setting and more likely to be associated with female gender, non-single, unemployed, less educated, and more severe depression. Previous reports also showed that patients with anxious depression had more frequent episodes of major depression and a higher risk of suicidal ideation and previous suicide attempts than those with non-anxious depression. Although anxious depression is known to be associated with poor treatment outcomes in several studies, recent researches have sought to find better treatment strategy to improve patients with anxious depression.

Oxytocin, a neuropeptide synthesized by the hypothalamus, plays a central role in human social behavior, social cognition, anxiety, mood, stress modulation, and fear learning and extinction. The relationships between oxytocin and psychiatric disorders including depression, anxiety, schizophrenia, and autism spectrum disorder have been extensively studied. In this chapter, we focus on the current knowledge about oxytocin and anxiety disorder. We discuss the anxiolytic effects of oxytocin in preclinical and clinical findings, possible related neurobehavioral mechanisms (social cognition, fear learning, and extinction), related neurotransmitter and neuroendocrine systems (hypothalamus-pituitary-adrenal axis, serotoninergic, and GABAergic systems), and studies regarding plasma levels of oxytocin, genetic and epigenetic findings, and effects of intranasal oxytocin in DSM-5 anxiety disorder (primarily social anxiety disorder and separation anxiety disorder) patients.

Under the partial influences of paradigm shift form category to dimension, the Diagnostic and Statistical Manual of Mental Disorder (DSM) was revised to the fifth edition (DSM-5); however, due to the lack of consistent biological makers and processes and the restricted availability of dimensional meta-structure, the revisions for the DSM-5 were based on a combination of categorical and dimensional approaches. Anxiety disorders were more clearly and consistently defined in the DSM-5 with the removal of obsessive compulsive, acute stress, and post-traumatic stress disorders. Differences between the childhood and adulthood categories of anxiety disorders were decreased, and overall, the symmetrical classification of anxiety subtypes was increased, since separation anxiety disorder and selective mutism were considered anxiety disorders, not neurodevelopmental disorders. Additionally, based on growing evidence, agoraphobia is distinct from panic disorder. Next, considering cultural syndromes including taijin kyofusho, khyal cap, trung gio attacks, and ataque de nervios, cultural influences are considered a significant factor for definitions and presentations of anxiety disorders. Controversies in the DSM-5 criteria for anxiety disorders are lowering the diagnostic thresholds of anxiety disorders and limiting the dichotomous view of anxiety and depression when defining generalized anxiety disorder. Further studies of alternative approaches to the restrictions of the DSM-5 criteria of anxiety disorders, including transdiagnostic specifiers and dimensional assessment tools, may be required.

The modern society is a so-called era of big data. Whereas nearly everybody recognizes the “era of big data”, no one can exactly define how big the data is a “big data”. The reason for the ambiguity of the term big data mainly arises from the widespread of using that term. Along the widespread application of the digital technology in the everyday life, a large amount of data is generated every second in relation with every human behavior (i.e., measuring body movements through sensors, texts sent and received via social networking services). In addition, nonhuman data such as weather and Global Positioning System signals has been cumulated and analyzed in perspectives of big data (Kan et al. in Int J Environ Res Public Health 15(4), 2018 [1]). The big data has also influenced the medical science, which includes the field of psychiatry (Monteith et al. in Int J Bipolar Disord 3(1):21, 2015 [2]). In this chapter, we first introduce the definition of the term “big data”. Then, we discuss researches which apply big data to solve problems in the clinical practice of psychiatry.

Recently, noninvasive brain stimulation (NIBS) methodologies, including TMS and tDCS, have been considered as efficacious, safe, and innovative treatments and alternatives to conventional therapies for some psychiatric disorders. Developing evidence suggests that applying rTMS and tDCS over the cognitive control network (CCN), particularly the dorsolateral prefrontal cortex (DLPFC), may improve core symptoms in various psychiatric disorders via direct impact on the cognitive control processes involved in emotion regulation. Therefore, neuromodulation of brain regions involved in the cognitive control of emotion by NIBS approaches could contribute to a paradigm shift in psychiatry. The available evidence suggests that development of effective treatment alternatives to enhance cognition is critical for patients with psychiatric disorders. The purpose of this chapter is to review the cognition-enhancing properties of tDCS and TMS and the impact of these treatments on cognitive control processes, especially those related to emotion regulation in psychiatric disorders.

Psychiatric disorders are too multifactorial to be defined as a primarily inflammatory disorder, and increased inflammatory response is not specific to mental disorder only. Numerous factors are involved in neuroinflammation, and there also are many confounding variables, making it difficult to obtain consistent outcomes. Therefore, it is necessary to specify genetic, physiological, and epidemiological attributes of particular population groups vulnerable to inflammatory response as well as the disease subtypes. As of now, definitive inflammatory markers for psychiatric disorders have not been identified, but they could be very useful in patients with minimal vulnerability. In addition, it is possible to use inflammatory markers as depression biomarkers in subtypes of depression, which can serve as bases to develop medications to treat the disorder.

Suicide is a serious public health problem in many countries and has always been a source of apprehension and quest to human mankind, which can be resolved with due diligence. Suicide is a hidden and silent epidemic, with many causative factors. Studying and researching on various causative factors have always been the subject of significance for the researchers. Psychiatric illnesses happen to be the primary reasons for the majority of suicide mortality cases. Not only this, there has been a consistent increase in the no. of cases of mental disorders as well as attempted and completed suicide cases. If one looks at global scenario, an approximate 70,000 people commit suicide, and further alarming is the fact that the rate of suicide attempt cases has gone up to 250% during last 18 years in conflict zones. Poisoning, hanging and self-immolation are some of the common methods to commit suicide. Physical and mental illness, disturbed emotional relationships and economic difficulties were the major reasons for suicide with the predisposed population being women, student and farmers. As per WHO’s approximation, there is one suicide every minute and an attempted suicide every third second. It implies that the number of killed due to suicide is greater than that of the ones killed due to the armed conflict.

Because of the poor link between psychiatric diagnosis and neurobiological findings, it is difficult to classify mental disorders. The changes made to psychiatric diagnostic systems over the years can be understood in terms of "practical conservatism." The Diagnostic and Statistical Manual of Mental Disorders (DSM)-I and DSM-II were theoretically supported by the psychoanalytic and psychodynamic approach. Subsequently, psychiatric diagnoses of this kind were opposed by the anti-psychiatry movement, as well as by the findings of the Rosenhan experiment. Thus, the DSM-III revolution contained more empiricism, aligning psychiatry with biomedicine. Psychiatric diagnoses are classified and defined in terms of Kraepelinian dualism, using a categorical approach. The empirical trend was continued in the DSM-IV. To overcome the limitations of current psychiatric diagnostic systems and integrate fundamental genetic, neurobiological, behavioral, environmental, and experimental components into psychiatry, the Research Domain Criteria (RDoC) were established. To overcome the limitations of the categorical approach, psychiatrists have considered adopting a dimensional approach. However, their efforts were frustrated in the DSM-5 revision process. Thus, the DSM-5 is characterized by the rearrangement of psychiatric diagnoses, the partial adoption of a dimensional approach, the introduction of new diagnoses, and harmonization with the International Classification of Diseases.

The biopsychosocial approach is a model of eclecticism, which consists of multidisciplinary academic fields, reacting against the "neuroscientification" of psychiatry. The biopsychosocial approach was proposed by George Engel following Adolf Meyer's psychobiological and Roy R. Ginker's eclectic approach to psychiatry. Although the use of the biopsychosocial approach is increasing, it has several limitations: First, specific practices cannot be guided by the biopsychosocial approach because it is considered to be "boundless psychiatry." Second, unlike an initial intention, the symptomatic use of psychotropic medications may be justified by the biopsychosocial approach. Third, the economic forces to enhance biological psychiatry cannot be hindered by the biopsychosocial approach. Hence, to overcome the limitations of the current biopsychosocial approach, potential new paradigms including evolutionary psychiatry, pragmatism, integrationism, and pluralism have been proposed. Above all, Eric Kandel presented the link between neuroscience and psychiatry from the perspective of integrationism. In accordance with integrationism and/or pluralism, based on the paradigm shift of the theoretical construct from chemical imbalance to dysfunctional circuit, next-generation treatments for mental disorders have been proposed by Thomas Insel. Thus, a more integrated biopsychosocial approach to managing psychiatric disorders including schizophrenia and panic disorder may be proposed.

Cognitive behavioral therapy for insomnia (CBT-I) is the treatment of choice for insomnia; however, it is not widely used due to a lack of experienced therapists and its relatively high clinical cost. Recently, Internet and mobile CBT-I have been developed to replace face-to-face CBT-I, and research on this topic has been increasing. In addition, attempts have been made to use wearable devices for sleep-wake estimation. Studies on digital CBT-I thus far have shown favorable treatment effects in general, but the problem of a high dropout rate has not been sufficiently improved. In addition, more sophisticated technology is needed to develop fully automated digital CBT-I. As part of efforts to maximize the treatment effectiveness of future insomnia patients, research and development of mobile and Internet CBT-I and improvement of sleep tracker accuracy and validation studies are needed.

Sleep and wake problems are comorbid in several psychiatric illnesses and are often important factors in treatment resistance. They are often experienced in clinical situations. For example, it is common to continue pharmacotherapy due to sleep problems, such as insomnia, after initial antidepressant treatment in depression. In chronic psychiatric disorders, sleep and related problems, such as insomnia, sleep apnea, restless legs syndrome, sleepiness, irregular circadian sleep-wake cycle, and prolonged and inappropriate hypnotic use, are commonly comorbid and often contribute to a treatment-resistant condition if not properly managed. Psychotropic medications frequently lead to sleep and wake problems in mental disorders. This review addresses the sleep and wake problems that are often comorbid in treatment-resistant psychiatric conditions and their cause and management.

Psychiatric patients with many episodes that do not respond satisfactorily to numerous sequential treatment regimens were included in the treatment resistance studies. Most studies have, however, used a post hoc experimental design that failed to determine the association between biomarkers and the initial risk of treatment-resistant psychiatric disorder (TRP). Such post hoc experimental design can be regarded only as a consequence of having treatment resistance, rather than being a causal risk factor for it. Although informative, data derived from such studies often do not allow for a distinction to be made between cause and effect. To deal with this problem, it is most ideal to enroll untreated patients (those who were diagnosed but have not yet undergone treatment) as study subjects. In this chapter, the authors will review methodological considerations to uncover initial biological risk factors for TRP and propose a better study design for future research by discussing the shortcomings of the traditional study design.

Integrated approaches for treatment-resistant psychiatric disorders can be an important issue in the perspective of clinical psychiatry. In the context of “next-generation treatments for psychiatric disorders,” the necessity for more precise and specific treatment approaches has been proposed. Hence, it has been suggested that treatment-resistant psychiatric disorders should be defined not by post hoc analyses but with clinical and biological markers. More specifically, the synergistic effect of interactions between specific genes and childhood trauma has been identified as a significant factor for defining treatment resistance in psychiatric disorders. Moreover, it has been consistently reported that antidepressant effects can interact with environmental factors. In addition, findings have supported the hypothetical conceptualization of an integrated approach to treatment-resistant psychiatric disorders. A new approach to psychotherapy, inspired by the reconsolidation-updating paradigm, which we refer to as the histone acetylation inhibitor-augmented psychotherapy (also called “plasticity-augmented psychotherapy”) is proposed. Hence, we speculate that the combination of psychotherapy and pharmacotherapy can be integrated from the viewpoint of epigenetic regulation and used to manage treatment-resistant psychiatric disorders in the future.

Although the genetic risk component for major depressive disorder (MDD) is considered to be substantial, genes do not directly encode for psychiatric symptoms. Therefore, intermediate phenotypes of neuroanatomical nature in MDD have been detected by imaging techniques. In order to evaluate the impact of genetic variation on behavior-related psychiatric symptoms, imaging genetics has been applied in various psychiatric disorders. Numerous studies have used magnetic resonance imaging to measure gray matter (GM) structure, white matter (WM) integrity and density, and functional metabolic activity patterns. This paper provides a comprehensive review of currently existing imaging genetics studies on MDD susceptibility gene polymorphisms (BDNF rs6265 (Val66Met), COMT rs4680 (Val158Met), MAOA-uVNTR, HTR1A rs6295 C(–1019)G, 5-HTTLPR, TPH2 rs4570625 (G-703T)), which have measured changes in GM structure, WM integrity, and functional abolic activity patterns of the brain.

Glutamate is one of the most abundant amino acids in the human brain. Glutamate is extensively involved in the metabolism and neurotransmission nearly in the entire regions of the brain. As the gradient of glutamate level between the intracellular and extracellular space is high, potent regulatory systems with glutamate receptors are required to maintain such gradient discrepancy. Maybe the most potent regulatory step in the modulation of the action of the glutamate is through excitatory amino acid transporters type 2 (EAAT2). Unlike other major neurotransmitter receptors such as serotonin, norepinephrine, and dopamine transporters, EAAT2 are mostly present in the membrane surface of the astrocytes. The initiation and termination of the glutamatergic cycle is mainly modulated in the tripartite synapses.

Evidence from pharmacological, neuroimaging, postmortem, and genetic studies underlines the various roles of 5-HT receptor subtypes in the pathogenesis of major depressive disorder. Recent investigations further supported the notion of their interaction with the antidepressant medication and advanced the knowledge on underlying mechanisms of their action. The heterogeneous properties of individual 5-HT receptors offer a chance for development of new generation of antidepressants, which may be more beneficial and effective than traditional selective serotonin reuptake inhibitors (SSRIs). Antagonists of 5-HT2A, 5-HT2C, 5-HT3, 5-HT6, and 5-HT7 receptors, as well as agonists of 5-HT1A, 5-HT1B, 5-HT2C, 5-HT4, and 5-HT6 receptors, were observed to produce antidepressant-like responses. Paradoxical antidepressant-like effects of both agonists and antagonists of 5-HT receptors are likely connected to the diverse neurochemical mechanisms they instantiate. Augmented behavioral effects of SSRIs and other antidepressants used in combined treatment with 5-HT receptor agonists or antagonists have also been reported. The involvement of 5-HT receptors in depression is complex. Identifying the role of 5-HT receptors in response to antidepressants is an essential step in recognizing their mechanisms of action and, thereby, potentially producing more effective antidepressants with fewer side effects in patients with major depressive disorder.

Melancholic depression is distinguished by a loss of appetite and sleep; melancholic patients are typically anxious and lose responsiveness to their environments. Those with melancholic depression tend to feel worse in the morning, while those with atypical depression generally feel worse in the evening.

Epidemiologic studies have revealed a twofold greater prevalence of depression in females than males. Frequently, the symptoms and comorbidities of depression also differ by gender. Many psychosocial factors and biological factors have been studied that may explain the different manifestations and prevalence of depression according to gender. Atypical symptoms, somatic symptoms, and parasuicidal behavior are more frequent in females. A male-specific depressive syndrome including acting out and increased impulsivity has been suggested. Anxiety disorder is more frequent in depressed females, whereas substance abuse is more frequent in males. Sociocultural factors, such as role restriction and discrimination in the workplace, certain traumas that occur more frequently in females (e.g., sexual assault), and coping style (e.g., rumination) appear to interact and contribute to the female predominance for depression. Still, most study findings and evidence regarding biological factors lack consistency and are insufficient for drawing conclusions. But gonadal hormones, the hypothalamic-pituitary-adrenal axis, and neurotransmitters seem to be closely related to each other and produce gender differences in depression. Especially, changes in gonadal hormones during the menstrual cycle, pregnancy, childbirth, and menopause appear to play key roles for some female-specific depressive syndromes.

Cognitive impairment in patients with depression has great clinical relevance, as depressed patients with cognitive impairment have more physical diseases, greater reduced social functionality, and, eventually, higher mortality. Although cognitive decline may simply be a symptom of depression, accurate assessment and treatment of cognitive impairment is crucial, as it is considered a key risk factor for the prognosis of possible neurocognitive disorders, such as Alzheimer’s disease. In this review, we investigated psychological and biological mechanisms of cognitive impairment in patients with depression and briefly discuss the methods to assess neurocognitive function in depression. Furthermore, we presented some issues about which to be cautious in the therapeutic setting.

In the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5), categorical and dimensional approaches to diagnose depressive disorders have been combined, resulting in the following changes: (1) mood disorders have been dichotomized into bipolar and related disorders and depressive disorders; (2) “hopelessness” has been added to the subjective descriptors of depressive mood; (3) disruptive mood dysregulation disorder (DMDD) and premenstrual dysphoric disorder (PMD) have been introduced as new distinct disease entities; (4) dysthymic disorder has been re-labeled as persistent depressive disorder (PDD); (5) the bereavement exclusion in the definition of major depressive disorder (MDD) has been removed; and (6) the specifiers “with psychotic features,” “with anxious stress,” “with mixed features,” “with peripartum onset,” and others have been revised and/or introduced. However, despite the presence of transnosological specifiers, severity assessments, and cross-cutting symptom measure assessments, depressive disorders in DSM-5 are still diagnosed and classified based largely on categorical approaches. Moreover, the heterogeneity of MDD in terms of a polythetic operational diagnosis has been characterized as corresponding to a language game in Wittgensteinian philosophy. Etiologically based diagnostic systems for depressive disorders that consider sociocultural influences on depressive symptomatology and that take a humanistic approach that considers subjective and interpersonal contexts need to be developed.

Current evidence supports the idea that a combination of pharmacotherapy and psychotherapy is superior for treating depression than each treatment alone. Here, we provide neurobiological explanations to advocate for combination therapy over each therapy alone, from the perspective of neuroplasticity. Furthermore, we assert that there is still room for improvement in this strategy. In psychotherapy, clinical practice can be improved based on our knowledge of memory reconsolidation. Memory retrieval-driven reconsolidation-updating processes enable past emotional memories to be updated by new information. In pharmacotherapy, different classes of pharmacologic agents, such as antidepressants and histone deacetylase (HDAC) inhibitors, are known to enhance neuroplasticity. A reconsolidation-targeted, time-limited combination of drugs will synergistically enhance neuroplasticity, safely and tolerably. Improving the accessibility of psychotherapeutic therapies with more flexibility in time and place is important.