Neuron-Microglia Crosstalk in Neuropsychiatric Disorders.

Numerous studies have investigated the causes and mechanisms of psychiatric disorders through postmortem examination of patients with a history of a schizophrenia, mood disorder, or neurocognitive disorder. In addition, the search for specific mechanism-based treatments for psychiatric disorders has been intensified through the use of transgenic animal models involving specific genes tightly associated with psychiatric disorders. As a result, many studies with patients or animal models have reported a close association of neuroglia with major psychiatric disorders. Recently, research has focused on the associations between microglia and major psychiatric disorders and on the role of the immune response and abnormal microglia in the onset and symptoms of psychiatric disorders, in particular. Postmortem studies of brain tissue and animal models recapitulating human mental disorders have also confirmed association between psychiatric disorders and quantitative, structural, or functional abnormalities of neuron-microglia crosstalk. This review aims to describe the relationships between microglia and major psychiatric disorders and to specifically examine studies of gene expression and function of microglia in depression, schizophrenia, and Alzheimer's disease.

Microbiota-Gut-Brain Axis: Pathophysiological Mechanism in Neuropsychiatric Disorders.

Gut microbiota influence human behavior. The immunological, metabolic, and endocrine systems are involved in bidirectional communication between the gut and the brain, which is regulated by microbes through the microbiota-derived neurochemicals and metabolites. Gut microbiota have certain effects on neurodevelopment and maturation of immunity. However, gut dysbiosis can lead to neuropsychiatric disorders. Animal research and clinical case-control studies have demonstrated that gut dysbiosis has an adverse effect on human behavior through a variety of mechanisms. Recent meta-analysis on clinical studies confirmed gut dysbiosis in several major neuropsychiatric disorders. Microbiota-targeted intervention has recently been in the spotlight and meta-analyses have confirmed its effectiveness. In this chapter, we summarize the evidence for the interactions between microbiota and brain-gut network, as well as the potential pathophysiological mechanisms involved.

Early Life Stress, Neuroinflammation, and Psychiatric Illness of Adulthood.

Stress exposure during early stages of life elevates the risk of developing psychopathologies and psychiatric illness in later life. The brain and immune system are not completely developed by birth and therefore continue develop after birth; this post birth development is influenced by several psychosocial factors; hence, early life stress (ELS) exposure can alter brain structural development and function. A growing number of experimental animal and observational human studies have investigated the link between ELS exposure and increased risk of psychopathology through alternations in the immune system, by evaluating inflammation biomarkers. Recent studies, including brain imaging, have also shed light on the mechanisms by which both the innate and adaptive immune systems interact with neural circuits and neurotransmitters, which affect psychopathology. Herein, we discuss the link between the experience of stress in early life and lifelong alterations in the immune system, which subsequently lead to the development of various psychiatric illnesses.

Molecular Imaging of Neuroinflammation in Alzheimer's Disease and Mild Cognitive Impairment.

Alzheimer's disease (AD) is the most prevalent neurocognitive disorder. Due to the ineffectiveness of treatments targeting the amyloid cascade, molecular biomarkers for neuroinflammation are attracting attention with increasing knowledge about the role of neuroinflammation in the pathogenesis of AD. This chapter will explore the results of studies using molecular imaging for diagnosing AD and mild cognitive impairment (MCI). Because it is critical to interpreting the data to understand which substances are targeted in molecular imaging, this chapter will discuss the two most significant targets, microglia and astrocytes, as well as the best-known radioligands for each. Then, neuroimaging results with PET neuroinflammation imaging will be reviewed for AD and MCI. Although a growing body of evidence has suggested that these molecular imaging biomarkers for neuroinflammation may have a role in the diagnosis of AD and MCI, the findings are inconsistent or cross-sectional, which indicates that it is difficult to apply the contents in practice due to the need for additional study. In particular, because the results of multiple interventions targeting neuroinflammation were inconclusive, molecular imaging markers for neuroinflammation can be used in combination with conventional markers to select appropriate patients for early intervention for neuroinflammation rather than as a single marker.

Microbiota-Gut-Brain Axis in Major Depression: A New Therapeutic Approach.

Major depression is impacted by the disruption of gut microbiota. Defects in gut microbiota can lead to microbiota-gut-brain axis dysfunction and increased vulnerability to major depression. While traditional chemotherapeutic approaches, such as antidepressant use, produce an overall partial therapeutic effect on depression, the gut microbiome has emerged as an effective target for better therapeutic outcomes. Recent representative studies on the microbiota hypothesis to explore the association between gut pathophysiology and major depression have indicated that restoring gut microbiota and microbiota-gut-brain axis could alleviate depression. We reviewed studies that supported the gut microbiota hypothesis to better understand the pathophysiology of depression; we also explored reports suggesting that gut microbiota restoration is an effective approach for improving depression. These findings indicate that gut microbiota and microbiota-gut-brain axis are appropriate new therapeutic targets for major depression.

Understanding the Connection Between the Gut-Brain Axis and Stress/Anxiety Disorders.

PURPOSE OF REVIEW: We review the association of the microbiota-gut-brain axis and anxiety disorder or stress. RECENT FINDING: The microbiota-gut-brain axis mechanism encompasses a bidirectional relationship between the brain and gastrointestinal organs. Dysregulation of the microbiota-gut-brain axis has been actively revealed in the context of various psychiatric diseases such as neurodevelopmental disorders, schizophrenia, anxiety disorders, and depression. We suggest that onset of anxiety disorders may be correlated with activation of a microbiota-gut-brain mechanism involving the immune system, neurotransmitters, and the hormonal system. By applying a microbiota-gut-brain axis mechanism, the possibility of using gastrointestinal system drugs such as probiotics and antibiotics as treatments for anxiety disorders is a possibility. Although modification of the microbiota-gut-brain axis mechanism has yet to be adopted clinically, it is expected that novel strategies employing this mechanism will be developed and deployed as new treatments not only for anxiety disorders, but also other psychiatric diseases.

Phenotype Network and Brain Structural Covariance Network of Major Depression.

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.

The Application of a Machine Learning-Based Brain Magnetic Resonance Imaging Approach in Major Depression.

Major depressive disorder (MDD) shows a high prevalence and is associated with increased disability. While traditional studies aimed to investigate global characteristic neurobiological substrates of MDD, machine learning-based approaches focus on individual people rather than a group. Therefore, machine learning has been increasingly conducted and applied to clinical practice. Several previous neuroimaging studies used machine learning for stratifying MDD patients from healthy controls as well as in differentially diagnosing MDD apart from other psychiatric disorders. Also, machine learning has been used to predict treatment response using magnetic resonance imaging (MRI) results. Despite the recent accomplishments of machine learning-based MRI studies, small sample sizes and the heterogeneity of the depression group limit the generalizability of a machine learning-based predictive model. Future neuroimaging studies should integrate various materials such as genetic, peripheral, and clinical phenotypes for more accurate predictability of diagnosis and treatment response.

Challenges and Strategies for Current Classifications of Depressive Disorders: Proposal for Future Diagnostic Standards.

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.

Development of Neuroimaging-Based Biomarkers in Major Depression.

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.

The Role of Neurotrophic Factors in Pathophysiology of Major Depressive Disorder.

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.

Associations between Melatonin, Neuroinflammation, and Brain Alterations in Depression.

Pro-inflammatory systemic conditions that can cause neuroinflammation and subsequent alterations in brain regions involved in emotional regulation have been suggested as an underlying mechanism for the pathophysiology of major depressive disorder (MDD). A prominent feature of MDD is disruption of circadian rhythms, of which melatonin is considered a key moderator, and alterations in the melatonin system have been implicated in MDD. Melatonin is involved in immune system regulation and has been shown to possess anti-inflammatory properties in inflammatory conditions, through both immunological and non-immunological actions. Melatonin has been suggested as a highly cytoprotective and neuroprotective substance and shown to stimulate all stages of neuroplasticity in animal models. The ability of melatonin to suppress inflammatory responses through immunological and non-immunological actions, thus influencing neuroinflammation and neurotoxicity, along with subsequent alterations in brain regions that are implicated in depression, can be demonstrated by the antidepressant-like effects of melatonin. Further studies that investigate the associations between melatonin, immune markers, and alterations in the brain structure and function in patients with depression could identify potential MDD biomarkers.

Gut Microbiota and Bipolar Disorder: An Overview on a Novel Biomarker for Diagnosis and Treatment.

The gut microbiota is the set of microorganisms that colonize the gastrointestinal tract of living creatures, establishing a bidirectional symbiotic relationship that is essential for maintaining homeostasis, for their growth and digestive processes. Growing evidence supports its involvement in the intercommunication system between the gut and the brain, so that it is called the gut-brain-microbiota axis. It is involved in the regulation of the functions of the Central Nervous System (CNS), behavior, mood and anxiety and, therefore, its implication in the pathogenesis of neuropsychiatric disorders. In this paper, we focused on the possible correlations between the gut microbiota and Bipolar Disorder (BD), in order to determine its role in the pathogenesis and in the clinical management of BD. Current literature supports a possible relationship between the compositional alterations of the intestinal microbiota and BD. Moreover, due to its impact on psychopharmacological treatment absorption, by acting on the composition of the microbiota beneficial effects can be obtained on BD symptoms. Finally, we discussed the potential of correcting gut microbiota alteration as a novel augmentation strategy in BD. Future studies are necessary to better clarify the relevance of gut microbiota alterations as state and disease biomarkers of BD.

Grey matter volume abnormalities in the first depressive episode of medication-naïve adult individuals: a systematic review of voxel based morphometric studies.

BACKGROUND: To identify the reliable and consistent grey matter volume (GMV) abnormalities associated with major depressive disorder (MDD), we excluded the influence of confounding clinical characteristics, comorbidities and brain degeneration on brain morphological abnormalities by inclusion of non-comorbid and non-geriatric drug-naïve MDD individuals experiencing first episode depressive. METHODS: The PubMed, Scopus, Web of Science, Science Direct and Google scholar databases were searched for papers published in English up to April 2020. RESULTS: A total of 21 voxel based morphometric (VBM) studies comparing 845 individuals in the first depressive episode and medication-naïve with 940 healthy control subjects were included. The results showed a grey matter volumes reductions in the orbitofrontal cortex (OFC), prefrontal cortex (PFC), frontal and temporal gyri, temporal pole, insular lobe, thalamus, basal ganglia, cerebellum, hippocampus, cingulate cortex, and amygdala. In addition, increased grey matter volumes in the postcentral gyrus, superior frontal gyrus, insula, basal ganglia, thalamus, amygdala, cuneus, and precuneus differentiated the first depressive episode in medication-naïve individuals from healthy subjects. CONCLUSION: The present systematic review provided additional support for the involvement of grey matter structural abnormalities in limbic-cortical circuits as possibly specific structural abnormalities in the early stage of MDD.Key pointsDistinct brain regions in MDD patients might be associated with the early stages of illness, and thus it is critical to study the causal relationship between brain structures and the onset of the disease to improve the evaluation in clinic.Grey matter alterations in the fronto-limbic networks in the first episode, medication-naïve MDD might suggest that these abnormalities may play an important role in the neuropathophysiology of MDD at its onset.First episode, medically naïve depressive patients show grey matter volume alterations in brain regions mainly associated with emotion regulation including parietal-temporal regions, PFC, insular lobe, thalamus, basal ganglia, cerebellum and limbic structures that may be specific changes in early stage of MDD.Genotype-diagnosis interaction effects on brain morphology in the cortico-limbic-striatal circuits, including the PFC, amygdala, hippocampus and striatum that might be implicated in the dysfunctional regulation of emotion in first-episode MDD patients.Future longitudinal and prospective studies should be conducted to identify the core structural brain changes in people at-risk for MDD and explore the association of their brain volumes with symptom onset.

Serum FAM19A5 levels: A novel biomarker for neuroinflammation and neurodegeneration in major depressive disorder.

Chronic low-grade inflammation contributes to the pathophysiology of major depressive disorder (MDD). This study aimed to examine the association between serum levels of FAM19A5, a novel chemokine-like peptide that reflects reactive astrogliosis and inflammatory activation in the brain, and the neurodegenerative changes of MDD by investigating the correlation between serum FAM19A5 levels and cortical thickness changes in patients with MDD. We included 52 drug-naïve patients with MDD and 60 healthy controls (HCs). Serum FAM19A5 levels were determined in peripheral venous blood samples using a sandwich enzyme-linked immunosorbent assay. All participants underwent T1-weighted structural magnetic resonance imaging. Serum FAM19A5 levels were greater in patients with MDD than in HCs. In the MDD group, there were significant inverse correlations between serum FAM19A5 levels and cortical thickness in the prefrontal regions (i.e., the left inferior and right medial superior frontal gyri), left posterior cingulate gyrus, right cuneus, and both precunei, which showed significantly reduced thickness in patients with MDD compared to HCs. However, no correlation between serum FAM19A5 level and cortical thickness was observed in the HC group. The results of our study indicate that serum FAM19A5 levels may reflect reactive astrogliosis and related neuroinflammation in MDD. Our findings also suggest that serum FAM19A5 may be a potential biomarker for the neurodegenerative changes of MDD.

The Role of the Oxytocin System in Anxiety Disorders.

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.

Phenotype Network and Brain Structural Covariance Network of Anxiety.

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.

Anxiety Disorders in the DSM-5: Changes, Controversies, and Future Directions.

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.

Comorbid Anxiety and Depression: Clinical and Conceptual Consideration and Transdiagnostic Treatment.

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.

Neuroinflammation-Associated Alterations of the Brain as Potential Neural Biomarkers in Anxiety Disorders.

Stress-induced changes in the immune system, which lead to neuroinflammation and consequent brain alterations, have been suggested as possible neurobiological substrates of anxiety disorders, with previous literature predominantly focusing on panic disorder, agoraphobia, and generalized anxiety disorder, among the anxiety disorders. Anxiety disorders have frequently been associated with chronic stress, with chronically stressful situations being reported to precipitate the onset of anxiety disorders. Also, chronic stress has been reported to lead to hypothalamic-pituitary-adrenal axis and autonomic nervous system disruption, which may in turn induce systemic proinflammatory conditions. Preliminary evidence suggests anxiety disorders are also associated with increased inflammation. Systemic inflammation can access the brain, and enhance pro-inflammatory cytokine levels that have been shown to precipitate direct and indirect neurotoxic effects. Prefrontal and limbic structures are widely reported to be influenced by neuroinflammatory conditions. In concordance with these findings, various imaging studies on panic disorder, agoraphobia, and generalized anxiety disorder have reported alterations in structure, function, and connectivity of prefrontal and limbic structures. Further research is needed on the use of inflammatory markers and brain imaging in the early diagnosis of anxiety disorders, along with the possible efficacy of anti-inflammatory interventions on the prevention and treatment of anxiety disorders.