Reduced hippocampal gray matter volume is a common feature of patients with major depression, bipolar disorder, and schizophrenia spectrum disorders

High-fat diet consumption promotes adolescent neurobehavioral abnormalities and hippocampal structural alterations via microglial overactivation accompanied by an elevated serum free fatty acid concentration

Mounting evidence suggests that high-fat diet (HFD) consumption increases the risk for depression, but the neurophysiological mechanisms involved remain to be elucidated. Here, we demonstrated that HFD feeding of C57BL/6J mice during the adolescent period (from 4 to 8 weeks of age) resulted in increased depression- and anxiety-like behaviors concurrent with changes in neuronal and myelin structure in the hippocampus. Additionally, we showed that hippocampal microglia in HFD-fed mice assumed a hyperactive state concomitant with increased PSD95-positive and myelin basic protein (MBP)-positive inclusions, implicating microglia in hippocampal structural alterations induced by HFD consumption. Along with increased levels of serum free fatty acids (FFAs), abnormal deposition of lipid droplets and increased levels of HIF-1α protein (a transcription factor that has been reported to facilitate cellular lipid accumulation) within hippocampal microglia were observed in HFD-fed mice. The use of minocycline, a pharmacological suppressor of microglial overactivation, effectively attenuated neurobehavioral abnormalities and hippocampal structural alterations but barely altered lipid droplet accumulation in the hippocampal microglia of HFD-fed mice. Coadministration of triacsin C abolished the increases in lipid droplet formation, phagocytic activity, and ROS levels in primary microglia treated with serum from HFD-fed mice. In conclusion, our studies demonstrate that the adverse influence of early-life HFD consumption on behavior and hippocampal structure is attributed at least in part to microglial overactivation that is accompanied by an elevated serum FFA concentration and microglial aberrations represent a potential preventive and therapeutic target for HFD-related emotional disorders.

Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample

There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.

Larger putamen in individuals at risk and with manifest bipolar disorder

BACKGROUND

Individuals at risk for bipolar disorder (BD) have a wide range of genetic and non-genetic risk factors, like a positive family history of BD or (sub)threshold affective symptoms. Yet, it is unclear whether these individuals at risk and those diagnosed with BD share similar gray matter brain alterations.

METHODS

In 410 male and female participants aged 17-35 years, we compared gray matter volume (3T MRI) between individuals at risk for BD (as assessed using the EPIbipolar scale; n = 208), patients with a DSM-IV-TR diagnosis of BD (n = 87), and healthy controls (n = 115) using voxel-based morphometry in SPM12/CAT12. We applied conjunction analyses to identify similarities in gray matter volume alterations in individuals at risk and BD patients, relative to healthy controls. We also performed exploratory whole-brain analyses to identify differences in gray matter volume among groups. ComBat was used to harmonize imaging data from seven sites.

RESULTS

Both individuals at risk and BD patients showed larger volumes in the right putamen than healthy controls. Furthermore, individuals at risk had smaller volumes in the right inferior occipital gyrus, and BD patients had larger volumes in the left precuneus, compared to healthy controls. These findings were independent of course of illness (number of lifetime manic and depressive episodes, number of hospitalizations), comorbid diagnoses (major depressive disorder, attention-deficit hyperactivity disorder, anxiety disorder, eating disorder), familial risk, current disease severity (global functioning, remission status), and current medication intake.

CONCLUSIONS

Our findings indicate that alterations in the right putamen might constitute a vulnerability marker for BD.

An Effect of Chronic Negative Stress on Hippocampal Structures and Functional Connectivity in Patients with Depressive Disorder

Purpose

Depressive disorder is a mental health disorder with complicated etiopathogenesis. Environmental stress and neurodevelopment combined with other factors contribute to the occurrence of depression. Especially for the depressive disorder with chronic negative stress, it has characteristics of recurrence and poor curative effect because of unclear mechanism. Here, we investigated the hippocampal structures and functional connectivity (FC) according to resting-state functional magnetic resonance imaging in patients with depression who underwent chronic negative stress.

Patients and Methods

A total of 65 patients with depression (34 underwent chronic negative stress and 31 non-underwent chronic negative stress) and 30 healthy controls who did not undergo chronic negative stress were included in the study. The volumes of hippocampal subfields, seed-based FCs between hippocampus and the whole brain voxels, and ROI-wise-based FC between hippocampal subfields were compared among the three groups.

Results

In the patients with depression who underwent chronic negative stress, the volumes of right_GC-ML-DG-head, right_CA4-head and right_CA3-head increased, FCs between Temporal_Mid_R, Precuneus_R, Frontal_Sup_R, Temporal_Sup_R, Angular_L, Frontal_Inf_Tri_R, Supp_Motor_Area_R, Precentral_L and hippocampus increased, and FCs between parasubiculum and CA3, and presubiculum and CA1 decreased. When compared to the patients who did not undergo chronic negative stress, the patients who underwent chronic negative stress had larger volumes of right_GC-ML-DG-head and right_CA3-head, higher FCs between Frontal_Sup_R, Frontal_Inf_Tri_R and hippocampus, and lower FCs between presubiculum and CA1.

Conclusion

The depression underwent chronic negative stress may experience disrupted hippocampal structures and functional connectivity. It may be one of potential depressive disorder subtypes.

Using a deep generation network reveals neuroanatomical specificity in hemispheres

Asymmetry is an important property of brain organization, but its nature is still poorly understood. Capturing the neuroanatomical components specific to each hemisphere facilitates the understanding of the establishment of brain asymmetry. Since deep generative networks (DGNs) have powerful inference and recovery capabilities, we use one hemisphere to predict the opposite hemisphere by training the DGNs, which automatically fit the built-in dependencies between the left and right hemispheres. After training, the reconstructed images approximate the homologous components in the hemisphere. We use the difference between the actual and reconstructed hemispheres to measure hemisphere-specific components due to asymmetric expression of environmental and genetic factors. The results show that our model is biologically plausible and that our proposed metric of hemispheric specialization is reliable, representing a wide range of individual variation. Together, this work provides promising tools for exploring brain asymmetry and new insights into self-supervised DGNs for representing the brain.

Contributions of Polygenic Risk and Disease Status to Gray Matter Abnormalities in Major Depression

BACKGROUND

Gray matter (GM) abnormalities in depression are potentially attributable to some combination of trait, state, and illness history factors. Here, we sought to determine the contributions of polygenic risk for depression, depressive disease status, and the interaction of these factors to these GM abnormalities.

METHODS

We conducted a cross-sectional comparison using a 2 × 3 factorial design examining effects of polygenic risk for depression (lower vs. upper quartile) and depression status (never depressed, currently depressed, or remitted depression) on regional GM concentration and GM volume. Participants were a subset of magnetic resonance imaging-scanned UK Biobank participants comprising 2682 people (876 men, 1806 women) algorithmically matched on 16 potential confounders.

RESULTS

In women but not men, we observed that elevated polygenic risk for depression was associated with reduced cerebellar GM volume. This deficit occurred in salience and dorsal attention network regions of the cerebellum and was associated with poorer performance on tests of attention and executive function but not fluid intelligence. Moreover, in women with current depression compared to both women with remitted depression and women who never had depression, we observed GM reductions in ventral and medial prefrontal, insular, and medial temporal regions. These state-related abnormalities remained when accounting for antidepressant medication status.

CONCLUSIONS

Neuroanatomical deficits attributed broadly to major depression are more likely due to an aggregation of independent factors. Polygenic risk for depression accounted for cerebellar structural abnormalities that themselves accounted for cognitive deficits observed in this disorder. Medial and ventral prefrontal, insular, and temporal cortex deficits constituted a much larger proportion of the aggregate deficit and were attributable to the depressed state.

Behavioral as well as hippocampal transcriptomic and microglial responses differ across sexes in adult mouse offspring exposed to a dual genetic and environmental challenge

INTRODUCTION

A wide range of positive, negative, and cognitive symptoms compose the clinical presentation of schizophrenia. Schizophrenia is a multifactorial disorder in which genetic and environmental risk factors interact for a full emergence of the disorder. Infectious challenges during pregnancy are a well-known environmental risk factor for schizophrenia. Also, genetic variants affecting the function of fractalkine signaling between neurons and microglia were linked to schizophrenia. Translational animal models recapitulating these complex gene-environment associations have a great potential to untangle schizophrenia neurobiology and propose new therapeutic strategies.

METHODS

Given that genetic variants affecting the function of fractalkine signaling between neurons and microglia were linked to schizophrenia, we compared the outcomes of a well-characterized model of maternal immune activation induced using the viral mimetic polyinosinic:polycytidylic acid (Poly I:C) in wild-type versus fractalkine receptor knockout mice. Possible behavioral and immune alterations were assessed in male and female offspring during adulthood. Considering the role of the hippocampus in schizophrenia, microglial analyses and bulk RNA sequencing were performed within this region to assess the neuroimmune dynamics at play. Males and females were examined separately.

RESULTS

Offspring exposed to the dual challenge paradigm exhibited symptoms relevant to schizophrenia and unpredictably to mood disorders. Males displayed social and cognitive deficits related to schizophrenia, while females mainly presented anxiety-like behaviors related to mood disorders. Hippocampal microglia in females exposed to the dual challenge were hypertrophic, indicative of an increased surveillance, whereas those in males showed on the other end of the spectrum blunted morphologies with a reduced phagocytosis. Hippocampal bulk-RNA sequencing further revealed a downregulation in females of genes related to GABAergic transmission, which represents one of the main proposed causes of mood disorders.

CONCLUSIONS

Building on previous results, we identified in the current study distinctive behavioral phenotypes in female mice exposed to a dual genetic and environmental challenge, thus proposing a new model of neurodevelopmentally-associated mood and affective symptoms. This paves the way to future sex-specific investigations into the susceptibility to developmental challenges using animal models based on genetic and immune vulnerability as presented here.

N-acetylcysteine during critical neurodevelopmental periods prevents behavioral and neurochemical deficits in the Poly I:C rat model of schizophrenia

Schizophrenia is a chronic neurodevelopmental disorder with an inflammatory/prooxidant component. N-acetylcysteine (NAC) has been evaluated in schizophrenia as an adjuvant to antipsychotics, but its role as a preventive strategy has not been sufficiently explored. We aimed to evaluate the potential of NAC administration in two-time windows before the onset of symptoms in a schizophrenia-like maternal immune stimulation (MIS) rat model. Pregnant Wistar rats were injected with Poly I:C or Saline on gestational day (GD) 15. Three different preventive approaches were evaluated: 1) NAC treatment during periadolescence in the offspring (from postnatal day [PND] 35 to 49); 2) NAC treatment during pregnancy after MIS challenge until delivery (GD15-21); and 3) NAC treatment throughout all pregnancy (GD1-21). At postnatal day (PND) 70, prepulse inhibition (PPI) and anxiety levels were evaluated. In vivo magnetic resonance (MR) imaging was acquired on PND100 to assess structural changes in gray and white matter, and brain metabolite concentrations. Additionally, inflammation and oxidative stress (IOS) markers were measured ex vivo in selected brain regions. MIS offspring showed behavioral, neuroanatomical, and biochemical alterations. Interestingly, NAC treatment during periadolescence prevented PPI deficits and partially counteracted some biochemical imbalances. Moreover, NAC treatments during pregnancy not only replicated the beneficial outcomes reported by the treatment in periadolescence, but also prevented some neuroanatomical deficits, including reductions in hippocampal and corpus callosum volumes. This study suggests that early reduction of inflammation and prooxidation could help prevent the onset of schizophrenia-like symptoms, supporting the importance of anti-IOS compounds in ameliorating this disorder.

Altered in vivo early neurogenesis traits in patients with depression: Evidence from neuron-derived extracellular vesicles and electroconvulsive therapy

BACKGROUND

The neurogenesis hypothesis is a promising candidate etiologic hypothesis for depression, and it is associated with electroconvulsive therapy (ECT). However, human in vivo molecular-level evidence is lacking.

OBJECTIVE

We used neuron-derived extracellular vesicles (NDEVs) as a "window to the neurons" to explore the in vivo neurogenesis status associated with ECT in patients with treatment-resistant depression (TRD).

METHODS

In this study, we enrolled 40 patients with TRD and 35 healthy controls (HCs). We isolated NDEVs from the plasma of each participant to test the levels of doublecortin (DCX), a marker of neurogenesis, and cluster of differentiation (CD) 81, a marker of EVs. We also assessed the plasma levels of brain-derived neurotrophic factor (BDNF), a protein that is known to be associated with ECT and neuroplastic processes.

RESULTS

Our findings indicated that both the levels of DCX in NDEVs and BDNF in plasma were significantly lower in TRD patients compared to HCs at baseline, but increased following ECTs. Conversely, levels of CD81 in NDEVs were found higher in TRD patients at baseline, but did not change after the ECT treatments. Exploratory analyses revealed that lower levels of BDNF in plasma and DCX in NDEVs, along with higher CD81 levels in NDEVs, were associated with more severe depressive symptoms and reduced cognitive function at baseline. Furthermore, higher baseline CD81 concentrations in NDEVs were correlated with greater decreases in depression symptoms.

CONCLUSIONS

We first present human in vivo evidence of early neurogenesis using DCX through NDEVs: decreased in TRD patients, increased after ECTs.

Five dominant dimensions of brain aging are identified via deep learning: associations with clinical, lifestyle, and genetic measures

Brain aging is a complex process influenced by various lifestyle, environmental, and genetic factors, as well as by age-related and often co-existing pathologies. MRI and, more recently, AI methods have been instrumental in understanding the neuroanatomical changes that occur during aging in large and diverse populations. However, the multiplicity and mutual overlap of both pathologic processes and affected brain regions make it difficult to precisely characterize the underlying neurodegenerative profile of an individual from an MRI scan. Herein, we leverage a state-of-the art deep representation learning method, Surreal-GAN, and present both methodological advances and extensive experimental results that allow us to elucidate the heterogeneity of brain aging in a large and diverse cohort of 49,482 individuals from 11 studies. Five dominant patterns of neurodegeneration were identified and quantified for each individual by their respective (herein referred to as) R-indices. Significant associations between R-indices and distinct biomedical, lifestyle, and genetic factors provide insights into the etiology of observed variances. Furthermore, baseline R-indices showed predictive value for disease progression and mortality. These five R-indices contribute to MRI-based precision diagnostics, prognostication, and may inform stratification into clinical trials.

Distinguishing functional and structural MRI abnormalities between bipolar and unipolar depression

Background

This study aims to investigate the underlying characteristics of spontaneous brain activity by analyzing the volumes of the hippocampus and parahippocampal gyrus, as well as the fractional amplitude of low-frequency fluctuation (fALFF) and regional homogeneity (ReHo), in order to differentiate between bipolar disorder (BD) and unipolar depressive disorder.

Methods

A total of 46 healthy controls, 58 patients with major depressive disorder (MDD), and 61 patients with BD participated in the study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. The researchers calculated the differences in volume, fALFF, and ReHo values among the three groups. Additionally, they conducted correlation analyses to examine the relationships between clinical variables and the aforementioned brain measures.

Results

The results showed that the BD group exhibited increased fALFF in the hippocampus compared to the healthy control (HC) and MDD groups. Furthermore, the ReHo values in the hippocampus and parahippocampal gyrus were significantly higher in the BD group compared to the HC group. The findings from the person correlation analysis indicated a positive relationship between ReHo values in the hippocampus and both HAMD and HAMA scores. Moreover, there was no correlation between the volumes, fALFF, and ReHo values in the hippocampus and parahippocampal gyrus, and cognitive function levels (RBANS).

Conclusion

Taken together, these aberrant patterns of intrinsic brain activity in the hippocampus and parahippocampal gyrus may serve as quantitative indicators for distinguishing between BD and unipolar depression.

Adult hippocampal neurogenesis: pharmacological mechanisms of antidepressant active ingredients in traditional Chinese medicine

Depression is characterized by prominent indicators and manifestations, such as anhedonia, which refers to the inability to experience pleasure, and persistent feelings of hopelessness. In clinical practice, the primary treatment approach involves the utilization of selective serotonin reuptake inhibitors (SSRIs) and related pharmacological interventions. Nevertheless, it is crucial to recognize that these agents are associated with significant adverse effects. Traditional Chinese medicine (TCM) adopts a multifaceted approach, targeting diverse components, multiple targets, and various channels of action. TCM has potential antidepressant effects. Anomalies in adult hippocampal neurogenesis (AHN) constitute a pivotal factor in the pathology of depression, with the regulation of AHN emerging as a potential key measure to intervene in the pathogenesis and progression of this condition. This comprehensive review presented an overview of the pharmacological mechanisms underlying the antidepressant effects of active ingredients found in TCM. Through examination of recent studies, we explored how these ingredients modulated AHN. Furthermore, we critically assessed the current limitations of research in this domain and proposed novel strategies for preclinical investigation and clinical applications in the treatment of depression in future.

Sleep Traits Causally Affect the Brain Cortical Structure: A Mendelian Randomization Study

Background: Brain imaging results in sleep deprived patients showed structural changes in the cerebral cortex; however, the reasons for this phenomenon need to be further explored. Methods: This MR study evaluated causal associations between morningness, ease of getting up, insomnia, long sleep, short sleep, and the cortex structure. Results: At the functional level, morningness increased the surface area (SA) of cuneus with global weighted (beta(b) (95% CI): 32.63 (10.35, 54.90), p = 0.004). Short sleep increased SA of the lateral occipital with global weighted (b (95% CI): 394.37(107.89, 680.85), p = 0.007. Short sleep reduced cortical thickness (TH) of paracentral with global weighted (OR (95% CI): -0.11 (-0.19, -0.03), p = 0.006). Short sleep reduced TH of parahippocampal with global weighted (b (95% CI): -0.25 (-0.42, -0.07), p = 0.006). No pleiotropy was detected. However, none of the Bonferroni-corrected p values of the causal relationship between cortical structure and the five types of sleep traits met the threshold. Conclusions: Our results potentially show evidence of a higher risk association between neuropsychiatric disorders and not only paracentral and parahippocampal brain areas atrophy, but also an increase in the middle temporal zone. Our findings shed light on the associations of cortical structure with the occurrence of five types of sleep traits.

Syntactic complexity and diversity of spontaneous speech production in schizophrenia spectrum and major depressive disorders

Syntax, the grammatical structure of sentences, is a fundamental aspect of language. It remains debated whether reduced syntactic complexity is unique to schizophrenia spectrum disorder (SSD) or whether it is also present in major depressive disorder (MDD). Furthermore, the association of syntax (including syntactic complexity and diversity) with language-related neuropsychology and psychopathological symptoms across disorders remains unclear. Thirty-four SSD patients and thirty-eight MDD patients diagnosed according to DSM-IV-TR as well as forty healthy controls (HC) were included and tasked with describing four pictures from the Thematic Apperception Test. We analyzed the produced speech regarding its syntax delineating measures for syntactic complexity (the total number of main clauses embedding subordinate clauses) and diversity (number of different types of complex sentences). We performed cluster analysis to identify clusters based on syntax and investigated associations of syntactic, to language-related neuropsychological (verbal fluency and verbal episodic memory), and psychopathological measures (positive and negative formal thought disorder) using network analyses. Syntax in SSD was significantly reduced in comparison to MDD and HC, whereas the comparison of HC and MDD revealed no significant differences. No associations were present between speech measures and current medication, duration and severity of illness, age or sex; the single association accounted for was education. A cluster analysis resulted in four clusters with different degrees of syntax across diagnoses. Subjects with less syntax exhibited pronounced positive and negative symptoms and displayed poorer performance in executive functioning, global functioning, and verbal episodic memory. All cluster-based networks indicated varying degrees of domain-specific and cross-domain connections. Measures of syntactic complexity were closely related while syntactic diversity appeared to be a separate node outside of the syntactic network. Cross-domain associations were more salient in more complex syntactic production.

Gait disorders in unipolar and bipolar depression

Objectives

Bipolar and unipolar depressions have a similar clinical picture, but different neurological and psychological mechanisms. These misleading similarities can lead to overdiagnosis and increased suicide risk. Recent studies show that gait is a sensitive objective marker for distinguishing the type of depression. The present study aims to compare psychomotor reactivity disorders and gait activity in unipolar and bipolar depression.

Methods

A total of 636 people aged 40.7 ± 11.2 years are studied with an ultrasound cranio-corpo-graph. They are divided into three groups - patients with unipolar depression, with bipolar depression and healthy controls. Each person performs three psychomotor tasks - a classic Unterberger task, a simplified version with open eyes and a complex version with an additional cognitive task.

Results

We find significant differences in psychomotor activity and reactivity between the three groups. Bipolar patients have more inhibited psychomotor skills than unipolar and they are both more inhibited than the norms. The simplified variant of the equilibriometric task is the most sensitive one and psychomotor reactivity is a more precise marker than psychomotor activity.

Conclusion

Both psychomotor activity and reactivity in gait could be sensitive markers for distinguishing similar psychiatric conditions. The application of the cranio-corpo-graph and the possible development of similar devices could lead to new diagnostic and therapeutic approaches, including early detection and prediction of the type of depression.

Rare coding variants as risk modifiers of the 22q11.2 deletion implicate postnatal cortical development in syndromic schizophrenia

22q11.2 deletion is one of the strongest known genetic risk factors for schizophrenia. Recent whole-genome sequencing of schizophrenia cases and controls with this deletion provided an unprecedented opportunity to identify risk modifying genetic variants and investigate their contribution to the pathogenesis of schizophrenia in 22q11.2 deletion syndrome. Here, we apply a novel analytic framework that integrates gene network and phenotype data to investigate the aggregate effects of rare coding variants and identified modifier genes in this etiologically homogenous cohort (223 schizophrenia cases and 233 controls of European descent). Our analyses revealed significant additive genetic components of rare nonsynonymous variants in 110 modifier genes (adjusted P = 9.4E-04) that overall accounted for 4.6% of the variance in schizophrenia status in this cohort, of which 4.0% was independent of the common polygenic risk for schizophrenia. The modifier genes affected by rare coding variants were enriched with genes involved in synaptic function and developmental disorders. Spatiotemporal transcriptomic analyses identified an enrichment of coexpression between modifier and 22q11.2 genes in cortical brain regions from late infancy to young adulthood. Corresponding gene coexpression modules are enriched with brain-specific protein-protein interactions of SLC25A1, COMT, and PI4KA in the 22q11.2 deletion region. Overall, our study highlights the contribution of rare coding variants to the SCZ risk. They not only complement common variants in disease genetics but also pinpoint brain regions and developmental stages critical to the etiology of syndromic schizophrenia.

Incorporating multi-stage diagnosis status to mine associations between genetic risk variants and the multi-modality phenotype network in major depressive disorder

Depression (major depressive disorder, MDD) is a common and serious medical illness. Globally, it is estimated that 5% of adults suffer from depression. Recently, imaging genetics receives growing attention and become a powerful strategy for discoverying the associations between genetic variants (e.g., single-nucleotide polymorphisms, SNPs) and multi-modality brain imaging data. However, most of the existing MDD imaging genetic research studies conducted by clinicians usually utilize simple statistical analysis methods and only consider single-modality brain imaging, which are limited in the deeper discovery of the mechanistic understanding of MDD. It is therefore imperative to utilize a powerful and efficient technology to fully explore associations between genetic variants and multi-modality brain imaging. In this study, we developed a novel imaging genetic association framework to mine the multi-modality phenotype network between genetic risk variants and multi-stage diagnosis status. Specifically, the multi-modality phenotype network consists of voxel node features and connectivity edge features from structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI). Thereafter, an association model based on multi-task learning strategy was adopted to fully explore the relationship between the MDD risk SNP and the multi-modality phenotype network. The multi-stage diagnosis status was introduced to further mine the relation among the multiple modalities of different subjects. A multi-modality brain imaging data and genotype data were collected by us from two hospitals. The experimental results not only demonstrate the effectiveness of our proposed method but also identify some consistent and stable brain regions of interest (ROIs) biomarkers from the node and edge features of multi-modality phenotype network. Moreover, four new and potential risk SNPs associated with MDD were discovered.

Postsynaptic Proteins at Excitatory Synapses in the Brain—Relationship with Depressive Disorders

Depressive disorders (DDs) are an increasingly common health problem that affects all age groups. DDs pathogenesis is multifactorial. However, it was proven that stress is one of the most important environmental factors contributing to the development of these conditions. In recent years, there has been growing interest in the role of the glutamatergic system in the context of pharmacotherapy of DDs. Thus, it has become increasingly important to explore the functioning of excitatory synapses in pathogenesis and pharmacological treatment of psychiatric disorders (including DDs). This knowledge may lead to the description of new mechanisms of depression and indicate new potential targets for the pharmacotherapy of illness. An excitatory synapse is a highly complex and very dynamic structure, containing a vast number of proteins. This review aimed to discuss in detail the role of the key postsynaptic proteins (e.g., NMDAR, AMPAR, mGluR5, PSD-95, Homer, NOS etc.) in the excitatory synapse and to systematize the knowledge about changes that occur in the clinical course of depression and after antidepressant treatment. In addition, a discussion on the potential use of ligands and/or modulators of postsynaptic proteins at the excitatory synapse has been presented.

Hippocampal circuit dysfunction in psychosis

Despite strong evidence of the neurodevelopmental origins of psychosis, current pharmacological treatment is not usually initiated until after a clinical diagnosis is made, and is focussed on antagonising striatal dopamine receptors. These drugs are only partially effective, have serious side effects, fail to alleviate the negative and cognitive symptoms of the disorder, and are not useful as a preventive treatment. In recent years, attention has turned to upstream brain regions that regulate striatal dopamine function, such as the hippocampus. This review draws together these recent data to discuss why the hippocampus may be especially vulnerable in the pathophysiology of psychosis. First, we describe the neurodevelopmental trajectory of the hippocampus and its susceptibility to dysfunction, exploring this region's proneness to structural and functional imbalances, metabolic pressures, and oxidative stress. We then examine mechanisms of hippocampal dysfunction in psychosis and in individuals at high-risk for psychosis and discuss how and when hippocampal abnormalities may be targeted in these groups. We conclude with future directions for prospective studies to unlock the discovery of novel therapeutic strategies targeting hippocampal circuit imbalances to prevent or delay the onset of psychosis.

The Role of Ketogenic Metabolic Therapy on the Brain in Serious Mental Illness: A Review

In search of interventions targeting brain dysfunction and underlying cognitive impairment in schizophrenia, we look at the brain and beyond to the potential role of dysfunctional systemic metabolism on neural network instability and insulin resistance in serious mental illness. We note that disrupted insulin and cerebral glucose metabolism are seen even in medication-naïve first-episode schizophrenia, suggesting that people with schizophrenia are at risk for Type 2 diabetes and cardiovascular disease, resulting in a shortened life span. Although glucose is the brain's default fuel, ketones are a more efficient fuel for the brain. We highlight evidence that a ketogenic diet can improve both the metabolic and neural stability profiles. Specifically, a ketogenic diet improves mitochondrial metabolism, neurotransmitter function, oxidative stress/inflammation, while also increasing neural network stability and cognitive function. To reverse the neurodegenerative process, increasing the brain's access to ketone bodies may be needed. We describe evidence that metabolic, neuroprotective, and neurochemical benefits of a ketogenic diet potentially provide symptomatic relief to people with schizophrenia while also improving their cardiovascular or metabolic health. We review evidence for KD side effects and note that although high in fat it improves various cardiovascular and metabolic risk markers in overweight/obese individuals. We conclude by calling for controlled clinical trials to confirm or refute the findings from anecdotal and case reports to address the potential beneficial effects of the ketogenic diet in people with serious mental illness.