Morphological changes in subregions of hippocampus and amygdala in major depressive disorder patients

Ethanol-Induced Depression: Exploring the Underlying Molecular Mechanisms

Ethanol consumption is widely recognized for its detrimental effects on mental health, particularly its association with depressive disorders. This narrative review aims to explore the intricate molecular mechanisms underlying ethanol-induced depression, synthesizing findings from preclinical and clinical studies. We begin by providing an overview of the relationship between chronic ethanol consumption and depression, highlighting compelling evidence from diverse populations. Subsequently, we delve into insights from animal models that elucidate the pathophysiological changes triggered by prolonged ethanol exposure. Key mechanisms identified include oxidative stress, which contributes to cellular damage; neuroinflammation, characterized by the activation of glial cells and altered cytokine profiles; and disruptions in neurotrophic factors that impair neuronal growth and survival. Furthermore, we discuss the induction of apoptosis in neural cells and the significant impact of ethanol on neurotransmitter receptor remodeling and regulation, leading to altered synaptic transmission. While substantial progress has been made in understanding these mechanisms, we also acknowledge the limitations of current research methodologies and call for further investigations to translate these findings into effective therapeutic strategies for individuals affected by ethanol-induced depression. This review ultimately underscores the need for a comprehensive understanding of the molecular underpinnings of ethanol's impact on mood disorders, paving the way for improved interventions and preventative measures.

HPA axis in psychotic and non-psychotic major depression: Cortisol plasma levels and hippocampal volume

BACKGROUND

Psychotic major depression (PMD) differs from non-psychotic MD (NPMD) in psychopathology and is linked to changes in brain volumetry and hypothalamic-pituitary-adrenal (HPA) axis function that can be reflected by its principal output - the glucocorticoid cortisol. NPMD patients exhibit smaller hippocampi than healthy controls (HC), purportedly representing exposure to chronic stress. However, the relationship between the individual clinical phenotype, hippocampal volume and diurnal cortisol signaling remains unclear.

METHODS

Since understanding the interplay among symptoms, neuroimaging and HPA function is crucial for discerning biological differences between PMD and NPMD, this study explored the link between clinical phenotype, hippocampal structural MRI and circadian plasma cortisol levels in 32 HC, 27 NPMD and 26 PMD patients.

RESULTS

PMD patients showed significantly elevated evening (6 p.m. - 1 a.m.) cortisol levels compared to NPMD and HC, while NPMD and HC did not differ. No group differences in hippocampal volume were observed, but a significant interaction effect emerged between overnight (1 a.m. - 9 a.m.) cortisol levels, hippocampal volume, and clinical phenotype. NPMD patients displayed a negative correlation between overnight cortisol levels and hippocampal volume, which was specific to the ascending cortisol curve (2 a.m. - 5 a.m.) and absent in PMD and HC. The hippocampus-cortisol interaction was associated with depressive symptom severity in NPMD but not PMD, where cortisol alone predicted greater severity.

CONCLUSIONS

These findings imply a time-dependent relationship between hippocampal volume and overnight cortisol in NPMD, which is absent in PMD and HC. In contrast, PMD patients exhibited increased evening cortisol levels. In an exploratory analysis, these effects were also related to symptom severity at similar timepoints. While correlational, these results point to distinct neurobiological mechanisms underlying NPMD and PMD, which are potentially related to the heterogeneous clinical manifestations.

Using dynamic graph convolutional network to identify individuals with major depression disorder

Objective and quantitative neuroimaging biomarkers are crucial for early diagnosis of major depressive disorder (MDD). However, previous studies using machine learning (ML) to distinguish MDD have often used small sample sizes and overlooked MDD's neural connectome and mechanism. To address these gaps, we applied Dynamic Graph Convolutional Nets (DGCNs) to a large multi-site dataset of 2317 resting state functional MRI (RS-fMRI) scans from 1081 MDD patients and 1236 healthy controls from 16 Rest-meta-MDD consortium sites. Our DGCN model combined with the personal whole brain functional connectivity (FC) network achieved an accuracy of 82.5 % (95 % CI:81.6-83.4 %, AUC:0.869), outperforming other universal ML classifiers. The most prominent domains for classification were mainly in the default mode network, fronto-parietal and cingulo-opercular network. Our study supports the stability and efficacy of using DGCN to characterize MDD and demonstrates its potential in enhancing neurobiological comprehension of MDD by detecting clinically related disorders in FC network topologies.

Basolateral amygdala volume in affective disorders using 7T MRI in vivo

Background

The basolateral complex of the amygdala is a crucial neurobiological site for Pavlovian conditioning. Investigations into volumetric alterations of the basolateral amygdala in individuals with major depressive disorder (MDD) have yielded conflicting results. These may be reconciled in an inverted U-shape allostatic growth trajectory. This hypothesized trajectory unfolds with an initial phase of volumetric expansion, driven by enhanced dendritic arborization and synaptic plasticity. The increase in volume is followed by a reduction phase, as glucocorticoid exposure cumulatively results in excitotoxic damage, reflecting allostatic load.

Methods

7T magnetic resonance brain imaging was conducted on a total of 84 participants (mean age 38 ± 12 years), comprising 20 unmedicated and 20 medicated individuals with MDD, 21 individuals suffering from bipolar disorder and 23 healthy controls. We employed FreeSurfer 7.3.2 for automatic high-resolution segmentation of nine amygdala subnuclei. We conducted analyses of covariance, with volumes of the basolateral complex, the lateral nucleus and, exploratively, the whole amygdala, as dependent variables, while controlling for the total intracranial volume and sex. Quadratic regressions were computed within the MDD group and in relevant subgroups to investigate the presence of a U-shaped relationship between the number of preceding major depressive episodes or the duration of the disease since the first episode and the dependent variables.

Results

Diagnostic groups did not exhibit statistically significant differences in the volumes of the basolateral amygdala (left F (3,75) = 0.66, p >.05; right F (3,76) = 1.80, p >.05), the lateral nucleus (left F (3,75) = 1.22, p >.05; right F (3,76) = 2.30, p >.05)), or the whole amygdala (left F (3,75) = 0.48, p >.05; right F (3,76) = 1.58, p >.05). No quadratic associations were observed between surrogate parameters of disease progression and any of the examined amygdala volumes. There were no significant correlations between subregion volumes and clinical characteristics.

Conclusion

We found no evidence for the hypothesis of an inverted U-shaped volumetric trajectory of the basolateral amygdala in MDD. Future research with larger sample sizes, including the measurement of genetic and epigenetic markers, will hopefully further elucidate this compelling paradigm.

Chemogenetic targeting TRPV1 in obesity-induced depression: Unveiling therapeutic potential of eicosapentaenoic acid and acupuncture

The comorbidity of obesity and depression has major public health impacts, highlighting the need to understand their shared mechanisms. This study explored the connection between obesity and depression through the transient receptor potential V1 (TRPV1) signaling pathway, using obese/depressed murine models and clinical data. Mice fed a high-fat diet showed altered TRPV1 pathway expression in brain regions of the mice: downregulated in the medial prefrontal cortex (mPFC) and hippocampus, and upregulated in the hypothalamus and amygdala, influencing depression-like behaviors and inflammation. Treatments like eicosapentaenoic acid (EPA) and acupoint catgut embedding (ACE) reversed these effects, similar to observations in Trpv1-/- mice. Furthermore, chemogenetic activation in the ventral mPFC also alleviated depression via TRPV1. In our clinical validation, single nucleotide polymorphisms (SNPs) in TRPV1-related genes (PIK3C2A and PRKCA) were linked to interferon-induced depression. These findings underscore the potential of targeting TRPV1 as a therapeutic approach for obesity-related depression.

MPGAN: Multi Pareto Generative Adversarial Network for the denoising and quantitative analysis of low-dose PET images of human brain

Positron emission tomography (PET) imaging is widely used in medical imaging for analyzing neurological disorders and related brain diseases. Usually, full-dose imaging for PET ensures image quality but raises concerns about potential health risks of radiation exposure. The contradiction between reducing radiation exposure and maintaining diagnostic performance can be effectively addressed by reconstructing low-dose PET (L-PET) images to the same high-quality as full-dose (F-PET). This paper introduces the Multi Pareto Generative Adversarial Network (MPGAN) to achieve 3D end-to-end denoising for the L-PET images of human brain. MPGAN consists of two key modules: the diffused multi-round cascade generator (GDmc) and the dynamic Pareto-efficient discriminator (DPed), both of which play a zero-sum game for n(n∈1,2,3) rounds to ensure the quality of synthesized F-PET images. The Pareto-efficient dynamic discrimination process is introduced in DPed to adaptively adjust the weights of sub-discriminators for improved discrimination output. We validated the performance of MPGAN using three datasets, including two independent datasets and one mixed dataset, and compared it with 12 recent competing models. Experimental results indicate that the proposed MPGAN provides an effective solution for 3D end-to-end denoising of L-PET images of the human brain, which meets clinical standards and achieves state-of-the-art performance on commonly used metrics.

Hippocampal subfield morphology from first episodes of bipolar disorder type II and major depressive disorder in a drug naïve Chinese cohort

INTRODUCTION

Symptoms during the onset of major depressive disorder [MDD] and bipolar disorder type II [BD-II] are similar. The difference of hippocampus subregion could be a biological marker to distinguish MDD from BD-II.

METHODS

We recruited 61 drug-naïve patients with a first-episode MDD and BD-II episode and 30 healthy controls (HC) to participate in a magnetic resonance imaging [MRI] study. We built a general linear model (one-way analysis of covariance) with 22 hippocampal subfields and two total hippocampal volumes as dependent variables, and the diagnosis of MDD, BD-II, and HC as independent variables. We performed pair-wise comparisons of hippocampal subfield volumes between MDD and HC, BD-II and MDD, BD-II and HC with post hoc for primary analysis.

RESULTS

We identified three regions that differed significantly in size between patients and controls. The left hippocampal fissure, the hippocampal-amygdaloid transition area (HATA), and the right subiculum body were all significantly larger in patients with MDD compared with the HC. In the onset of first-episode of MDD, the hippocampal volume increased significantly, especially on the left side comparing to HC. However, we found differences between MDD and BD-II were not statistically significant. The volume of the left HATA and right subiculum body in BD-II was larger.

CONCLUSIONS

The sample size of this study is relatively small, as it is a cross-sectional comparative study. In both MDD and BD-II groups, the volume of more left subregions appeared to increase. The left subregions were severely injured in the development of depressive disorder.

Divergent effects of sex on hippocampal subfield alterations in drug-naive patients with major depressive disorder

BACKGROUND

The hippocampus is a crucial brain structure in etiological models of major depressive disorder (MDD). It remains unclear whether sex differences in the incidence and symptoms of MDD are related to differential illness-associated brain alterations, including alterations in the hippocampus. This study investigated divergent the effects of sex on hippocampal subfield alterations in drug-naive patients with MDD.

METHODS

High-resolution structural MR images were obtained from 144 drug-naive individuals with MDD early in their illness course and 135 age- and sex-matched healthy controls (HCs). Hippocampal subfields were segmented using FreeSurfer software and analyzed in terms of both histological subfields (CA1-4, dentate gyrus, etc.) and more integrative larger functional subregions (head, body and tail).

RESULTS

We observed a significant overall reduction in hippocampal volume in MDD patients, with deficits more prominent deficits in the posterior hippocampus. Differences in anatomic alterations between male and female patients were observed in the CA1-head, presubiculum-body and fimbria in the left hemisphere. Exploratory analyses revealed different patterns of clinical and memory function correlations with histological subfields and functional subregions between male and female patients primarily in the hippocampal head and body.

LIMITATIONS

This cross-sectional study cannot clarify the causality of hippocampal alterations or their association with illness risk or onset.

CONCLUSIONS

These findings represent the first reported sex-specific alterations in hippocampal histological subfields in patients with MDD early in the illness course prior to treatment. Sex-specific hippocampal alterations may contribute to diverse sex differences in the clinical presentation of MDD.

Atrophy patterns in hippocampus and amygdala subregions of depressed patients with Parkinson's disease

We aimed to explore the subregional atrophy patterns of the amygdala and hippocampus in Parkinson's disease (PD) with depression and their correlation with the severity of the depressive symptom. MRI scans were obtained for 34 depressed PD patients (DPD), 22 nondepressed PD patients (NDPD), and 28 healthy controls (HC). Amygdala and hippocampal subregions were automatically segmented, and the intergroup volume difference was compared. The relationships between the volumes of the subregions and depression severity were investigated. Logistic analysis and Receiver operator characteristic curve were used to find independent predictors of DPD. Compared with the HC group, atrophy of the bilateral lateral nucleus, left accessory basal nucleus, right cortical nucleus, right central nucleus, and right medial nucleus subregions of the amygdala were visible in the DPD group, while the right lateral nucleus subregion of the amygdala was smaller in the DPD group than in the NDPD group. The DPD group showed significant atrophy in the left molecular layer, left GC-DG, left CA3, and left CA4 subregions compared with the HC group for hippocampal subregion volumes. Also, the right lateral nuclei volume and disease duration were independent predictors of DPD. To sum up, DPD patients showed atrophy in multiple amygdala subregions and left asymmetric hippocampal subregions. The decreased amygdala and hippocampal subregion volumes were correlated with the severity of depressive symptoms. The volume of right lateral nuclei and disease duration could be used as a biomarker to detect DPD.

Reduced gray matter volume of the hippocampal tail in melancholic depression: evidence from an MRI study

BACKGROUND

Melancholic depression (MD) is one of the most prevalent and severe subtypes of major depressive disorder (MDD). Previous studies have revealed inconsistent results regarding alterations in grey matter volume (GMV) of the hippocampus and amygdala of MD patients, possibly due to overlooking the complexity of their internal structure. The hippocampus and amygdala consist of multiple and functionally distinct subregions, and these subregions may play different roles in MD. This study aims to investigate the volumetric alterations of each subregion of the hippocampus and amygdala in patients with MD and non-melancholic depression (NMD).

METHODS

A total of 146 drug-naïve, first-episode MDD patients (72 with MD and 74 with NMD) and 81 gender-, age-, and education-matched healthy controls (HCs) were included in the study. All participants underwent magnetic resonance imaging (MRI) scans. The subregional segmentation of hippocampus and amygdala was performed using the FreeSurfer 6.0 software. The multivariate analysis of covariance (MANCOVA) was used to detect GMV differences of the hippocampal and amygdala subregions between three groups. Partial correlation analysis was conducted to explore the relationship between hippocampus or amygdala subfields and clinical characteristics in the MD group. Age, gender, years of education and intracranial volume (ICV) were included as covariates in both MANCOVA and partial correlation analyses.

RESULTS

Patients with MD exhibited a significantly lower GMV of the right hippocampal tail compared to HCs, which was uncorrelated with clinical characteristics of MD. No significant differences were observed among the three groups in overall and subregional GMV of amygdala.

CONCLUSIONS

Our findings suggest that specific hippocampal subregions in MD patients are more susceptible to volumetric alterations than the entire hippocampus. The reduced right hippocampal tail may underlie the unique neuropathology of MD. Future longitudinal studies are required to better investigate the associations between reduced right hippocampal tail and the onset and progression of MD.

Correlation studies of Hippocampal Morphometry and Plasma NFL Levels in Cognitively Unimpaired Subjects

Alzheimer's disease(AD) is being the burden of society and family. Applying computing-aided strategies to reveal its pathology is one of the research highlights. Plasma neurofilament light (NFL) is an emerging noninvasive and economic biomarker for AD molecular pathology. It is valuable to reveal the correlations between the plasma NFL levels and neurodegeneration, especially hippcampal deformations at the preclinical stage. The negative correlation between plasma NFL levels and hippocampal volumes has been documented. However, the relationship between the plasma NFL levels and the hippocampal morphometry details at the preclinical stage is still elusive. This study seeks to demonstrate the capacity of our proposed surface-based hippocampal morphometry system to discern the plasma NFL positive (NFL+>41.9 pg/L) level and plasma NFL negative (NFL-<41.9pg/L) level and illustrate its superiority to the hippocampal volume measurement by drawing the cohort of 154 CU middle aged and elderly adults. We also apply this morphometry measure and a proposed sparse coding based classification algorithm to classify CU individuals with NFL+ and NFL- levels. Experimental results show that the proposed hippocampal morphometry system offers stronger statistical power to discriminate CU subjects with NFL+ and NFL- levels, comparing with the hippocampal volume measure. Furthermore, this system can discriminate plasma NFL levels in CU individuals (Accuracy=0.86). Both the group level and individual level analysis results indicate that the association between plasma NFL levels and the hippocampal shapes can be mapped at the preclinical stage.

Differential alterations of amygdala nuclei volumes in acutely ill patients with anorexia nervosa and their associations with leptin levels

BACKGROUND

The amygdala is a subcortical limbic structure consisting of histologically and functionally distinct subregions. New automated structural magnetic resonance imaging (MRI) segmentation tools facilitate the in vivo study of individual amygdala nuclei in clinical populations such as patients with anorexia nervosa (AN) who show symptoms indicative of limbic dysregulation. This study is the first to investigate amygdala nuclei volumes in AN, their relationships with leptin, a key indicator of AN-related neuroendocrine alterations, and further clinical measures.

METHODS

T1-weighted MRI scans were subsegmented and multi-stage quality controlled using FreeSurfer. Left/right hemispheric amygdala nuclei volumes were cross-sectionally compared between females with AN (n = 168, 12-29 years) and age-matched healthy females (n = 168) applying general linear models. Associations with plasma leptin, body mass index (BMI), illness duration, and psychiatric symptoms were analyzed via robust linear regression.

RESULTS

Globally, most amygdala nuclei volumes in both hemispheres were reduced in AN v. healthy control participants. Importantly, four specific nuclei (accessory basal, cortical, medial nuclei, corticoamygdaloid transition in the rostral-medial amygdala) showed greater volumetric reduction even relative to reductions of whole amygdala and total subcortical gray matter volumes, whereas basal, lateral, and paralaminar nuclei were less reduced. All rostral-medially clustered nuclei were positively associated with leptin in AN independent of BMI. Amygdala nuclei volumes were not associated with illness duration or psychiatric symptom severity in AN.

CONCLUSIONS

In AN, amygdala nuclei are altered to different degrees. Severe volume loss in rostral-medially clustered nuclei, collectively involved in olfactory/food-related reward processing, may represent a structural correlate of AN-related symptoms. Hypoleptinemia might be linked to rostral-medial amygdala alterations.

Volumes of hippocampal subfields suggest a continuum between schizophrenia, major depressive disorder and bipolar disorder

Objective

There is considerable debate as to whether the continuum of major psychiatric disorders exists and to what extent the boundaries extend. Converging evidence suggests that alterations in hippocampal volume are a common sign in psychiatric disorders; however, there is still no consensus on the nature and extent of hippocampal atrophy in schizophrenia (SZ), major depressive disorder (MDD) and bipolar disorder (BD). The aim of this study was to verify the continuum of SZ - BD - MDD at the level of hippocampal subfield volume and to compare the volume differences in hippocampal subfields in the continuum.

Methods

A total of 412 participants (204 SZ, 98 MDD, and 110 BD) underwent 3 T MRI scans, structured clinical interviews, and clinical scales. We segmented the hippocampal subfields with FreeSurfer 7.1.1 and compared subfields volumes across the three diagnostic groups by controlling for age, gender, education, and intracranial volumes.

Results

The results showed a gradual increase in hippocampal subfield volumes from SZ to MDD to BD. Significant volume differences in the total hippocampus and 13 of 26 hippocampal subfields, including CA1, CA3, CA4, GC-ML-DG, molecular layer and the whole hippocampus, bilaterally, and parasubiculum in the right hemisphere, were observed among diagnostic groups. Medication treatment had the most effect on subfields of MDD compared to SZ and BD. Subfield volumes were negatively correlated with illness duration of MDD. Positive correlations were found between subfield volumes and drug dose in SZ and MDD. There was no significant difference in laterality between diagnostic groups.

Conclusion

The pattern of hippocampal volume reduction in SZ, MDD and BD suggests that there may be a continuum of the three disorders at the hippocampal level. The hippocampus represents a phenotype that is distinct from traditional diagnostic strategies. Combined with illness duration and drug intervention, it may better reflect shared pathophysiology and mechanisms across psychiatric disorders.

Cross-sectional field study comparing hippocampal subfields in patients with post-traumatic stress disorder, major depressive disorder, post-traumatic stress disorder with comorbid major depressive disorder, and adjustment disorder using routine clinical data

Background

The hippocampus is a central brain structure involved in stress processing. Previous studies have linked stress-related mental disorders, such as post-traumatic stress disorder (PTSD) and major depressive disorder (MDD), with changes in hippocampus volume. As PTSD and MDD have similar symptoms, clinical diagnosis relies solely on patients reporting their cognitive and emotional experiences, leading to an interest in utilizing imaging-based data to improve accuracy. Our field study aimed to determine whether there are hippocampal subfield volume differences between stress-related mental disorders (PTSD, MDD, adjustment disorders, and AdjD) using routine clinical data from a military hospital.

Methods

Participants comprised soldiers (N = 185) with PTSD (n = 50), MDD (n = 70), PTSD with comorbid MDD (n = 38), and AdjD (n = 27). The hippocampus was segmented and volumetrized into subfields automatically using FreeSurfer. We used ANCOVA models with estimated total intracranial volume as a covariate to determine whether there were volume differences in the hippocampal subfields cornu ammonis 1 (CA1), cornu ammonis 2/3 (CA2/3), and dentate gyrus (DG) among patients with PTSD, MDD, PTSD with comorbid MDD, and AdjD. Furthermore, we added self-reported symptom duration and previous psychopharmacological and psychotherapy treatment as further covariates to examine whether there were associations with CA1, CA2/3, and DG.

Results

No significant volume differences in hippocampal subfields between stress-related mental disorders were found. No significant associations were detected between symptom duration, psychopharmacological treatment, psychotherapy, and the hippocampal subfields.

Conclusion

Hippocampal subfields may distinguish stress-related mental disorders; however, we did not observe any subfield differences. We provide several explanations for the non-results and thereby inform future field studies.

Every individual makes a difference: A trinity derived from linking individual brain morphometry, connectivity and mentalising ability

Mentalising ability, indexed as the ability to understand others' beliefs, feelings, intentions, thoughts and traits, is a pivotal and fundamental component of human social cognition. However, considering the multifaceted nature of mentalising ability, little research has focused on characterising individual differences in different mentalising components. And even less research has been devoted to investigating how the variance in the structural and functional patterns of the amygdala and hippocampus, two vital subcortical regions of the "social brain", are related to inter-individual variability in mentalising ability. Here, as a first step toward filling these gaps, we exploited inter-subject representational similarity analysis (IS-RSA) to assess relationships between amygdala and hippocampal morphometry (surface-based multivariate morphometry statistics, MMS), connectivity (resting-state functional connectivity, rs-FC) and mentalising ability (interactive mentalisation questionnaire [IMQ] scores) across the participants ( N = 24 $$ N=24 $$ ). In IS-RSA, we proposed a novel pipeline, that is, computing patching and pooling operations-based surface distance (CPP-SD), to obtain a decent representation for high-dimensional MMS data. On this basis, we found significant correlations (i.e., second-order isomorphisms) between these three distinct modalities, indicating that a trinity existed in idiosyncratic patterns of brain morphometry, connectivity and mentalising ability. Notably, a region-related mentalising specificity emerged from these associations: self-self and self-other mentalisation are more related to the hippocampus, while other-self mentalisation shows a closer link with the amygdala. Furthermore, by utilising the dyadic regression analysis, we observed significant interactions such that subject pairs with similar morphometry had even greater mentalising similarity if they were also similar in rs-FC. Altogether, we demonstrated the feasibility and illustrated the promise of using IS-RSA to study individual differences, deepening our understanding of how individual brains give rise to their mentalising abilities.

Abnormal white matter integrity in Papez circuit in first-episode medication-naive adults with anxious depression: A combined voxel-based analysis and region of interest study

BACKGROUND

Anxious depression is one of the subtypes of major depressive disorder (MDD), usually defined as "patients with MDD and high levels of anxiety symptoms". Compared to non-anxious MDD (naMDD), patients with anxious MDD (aMDD) have more severe depressive symptoms and suicidal ideation, worse treatment outcomes and remission rates, and poorer prognosis. Current research suggests that the Papez circuit is an important brain structure closely related to emotion, memory, and cognition. This study applied DTI to explore the altered white matter integrity in Papez circuit of patients with aMDD.

METHODS

DTI data were acquired from 30 medication-naive outpatients with naMDD and 55 with aMDD and 88 demographically similar healthy control (HC) subjects. Voxel-based analysis (VBM) and region of interest (ROI) analysis were conducted to explore the significant difference of fractional anisotropy (FA) values among 3 groups. Pearson's correlations were performed to analyze the correlation between FA values and the score of HAMA-14 and HAMD-17.

RESULTS

We found that aMDD patients had significantly higher FA values in left fornix (belong to Papez circuit) and left posterior thalamic radiation and right anterior corona radiata (belong to limbic-thalamo-cortical circuitry) compared with HC. And there was variability in the white matter integrity in right posterior thalamic radiation (belong to limbic-thalamo-cortical circuitry) and left fornix (belong to Papez circuit) between aMDD and naMDD patients.

LIMITATIONS

The cross-sectional study and the population vary between aMDD group and naMDD group are limitations.

CONCLUSIONS

Abnormal white matter integrity in Papez circuit and Limbic-Thalamo-Cortical circuitry may play an important role in the neuropathology of aMDD and might help to identify aMDD.

Periodic limb movements in sleep are linked to decreased hippocampus and amygdala volumes in the population-based BiDirect Study

STUDY OBJECTIVES

Even though numerous studies indicate that sleep disorders are associated with altered brain morphology, MRI studies focusing on periodic limb movements in sleep (PLMS) are scarce. Our aim was to investigate the association of PLMS with global and regional gray matter volumes as well as white matter hyperintensity (WMH) volume.

METHODS

One hundred and eighty-nine subjects (57.0 ± 7.8 years, women: 50.5%) of the population-based BiDirect Study underwent a single-night polysomnography (PSG). Standard criteria of the American Academy of Sleep Medicine were applied to evaluate sleep characteristics and calculate the PLMS index (PLMSI). T1w and FLAIR images were acquired with cerebral MRI at 3 Tesla. Voxel-based morphometry was performed to determine the total gray matter volume as well as the volume of cortical segments and subcortical gray matter areas using SPM12 and CAT12. The WMH volume was quantified with the Brain Intensity AbNormality Classification Algorithm. The independent relationship between MRI markers and PLMSI was analyzed using multivariable linear regression with adjustment for age, sex, body mass index, intracranial volume, PSG scorer, PSG device, sleep apnea, and the use of antidepressants.

RESULTS

PLMSI was not significantly related to global gray matter volume and WMH volume. However, significant inverse associations of the PLMSI with the volume of the hippocampus (left and right hemisphere) and left amygdala were observed.

CONCLUSIONS

A significant relationship between a higher PLMSI and lower volumes of the hippocampus and amygdala was found among the participants of the BiDirect Study. Since these associations are based on exploratory analyses, further replications are required before drawing firm conclusions.

Structural covariance network of the hippocampus-amygdala complex in medication-naïve patients with first-episode major depressive disorder

Background

The hippocampus and amygdala are densely interconnected structures that work together in multiple affective and cognitive processes that are important to the etiology of major depressive disorder (MDD). Each of these structures consists of several heterogeneous subfields. We aim to explore the topologic properties of the volume-based intrinsic network within the hippocampus-amygdala complex in medication-naïve patients with first-episode MDD.

Methods

High-resolution T1-weighted magnetic resonance imaging scans were acquired from 123 first-episode, medication-naïve, and noncomorbid MDD patients and 81 age-, sex-, and education level-matched healthy control participants (HCs). The structural covariance network (SCN) was constructed for each group using the volumes of the hippocampal subfields and amygdala subregions; the weights of the edges were defined by the partial correlation coefficients between each pair of subfields/subregions, controlled for age, sex, education level, and intracranial volume. The global and nodal graph metrics were calculated and compared between groups.

Results

Compared with HCs, the SCN within the hippocampus-amygdala complex in patients with MDD showed a shortened mean characteristic path length, reduced modularity, and reduced small-worldness index. At the nodal level, the left hippocampal tail showed increased measures of centrality, segregation, and integration, while nodes in the left amygdala showed decreased measures of centrality, segregation, and integration in patients with MDD compared with HCs.

Conclusion

Our results provide the first evidence of atypical topologic characteristics within the hippocampus-amygdala complex in patients with MDD using structure network analysis. It provides more delineate mechanism of those two structures that underlying neuropathologic process in MDD.

Antidepressant-like potential of silymarin and silymarin-sertraline combination in mice: Highlighting effects on behaviour, oxidative stress, and neuroinflammation

BACKGROUND

Currently, there is increasing advocacy for the use of diet, dietary supplements, and herbal remedies in depression management.

AIM

To determine the antidepressant effects of standardized silymarin (SILY) extract either as a sole agent or as an adjunct in depression therapy.

METHODS

Adult mice were assigned into three main groups based on the neurobehavioural models; and each main group had ten treatment groups of 10 mice each. Treatment groups were: Vehicle control group, oral sertraline (SERT) group, two groups fed SILY)-supplemented diet (SILY at 140 and 280 mg/kg of feed, respectively), dexamethasone (DEX; i.p.) group, DEX/SERT group, two groups of DEX/SILY (SILY at 140 and 280 mg/kg of feed, respectively), and another two groups of (SERT/DEX/SILY) (SILY at 140 and 280 mg/kg of feed, respectively, plus i.p. DEX plus SERT). Duration of the study was 7 wk, and treatments were administered daily.

RESULTS

SILY (alone) increased body weight, open field locomotor activity, rearing, and grooming; it also enhanced spatial working memory while decreasing anxiety-related behaviours and behavioural despair. SILY also improved antioxidant status while decreasing lipid peroxidation, acetylcholinesterase activity, and inflammatory markers. Neuronal integrity of the cerebral cortex and hippocampus was preserved. Overall, when administered alone or with SERT, SILY counteracted DEX-induced behavioural and biochemical changes while preserving neuromorphological integrity.

CONCLUSION

In conclusion, SILY is beneficial in mitigating DEX-induced central nervous system and other related changes in mice.

Tanshinone IIA ameliorates chronic unpredictable mild stress-induced depression-like behavior and cognitive impairment in rats through the BDNF/TrkB/GAT1 signaling pathway

BACKGROUND

Depression is a common disorder with a complex pathogenesis. Tanshinone IIA (TAN IIA) is a botanical agent with neuroprotective and antidepressant properties.

OBJECTIVE

To examine the effects of TAN IIA on chronic unpredictable mild stress (CUMS)-induced depression-like behavior and cognitive impairment in rats.

METHODS

Rats were exposed to CUMS for 4 weeks, followed by the oral administration of TAN IIA, Deanxit (DEAN), or normal saline for an additional 4 weeks. The control rats were fed with regular chow and administered with normal saline for 4 weeks. Behavioral tests were performed to assess the effects of TAN IIA on depression-like behavior and cognitive impairment in rats with CUMS. The morphology of dendrites was analyzed by Golgi staining. Immunofluorescence staining was performed to determine protein localization.

RESULTS

TAN IIA treatment ameliorated CUMS-induced depression-like behavior and cognitive impairment in rats. TAN IIA treatment also reversed the effects of CUMS on dendritic complexity and the levels of gamma-aminobutyric acid (GABA) in the hippocampus and prefrontal cortex. Rats with CUMS showed decreased levels of brain-derived neurotrophic factor (BDNF) and phosphorylated tropomyosin receptor kinase B (TrkB), upregulated expression of GABA transporter 1 (GAT1), and reduced expression of synaptic proteins in the hippocampus, while TAN IIA treatment significantly diminished the effects of CUMS exposure. In addition, GAT1 was colocalized with N-methyl-D-aspartate receptor 2B.

CONCLUSION

TAN IIA ameliorates CUMS-induced depression-like behavior and cognitive impairment in rats by regulating the BDNF/TrkB/GAT1 signaling pathway, suggesting that TAN IIA may be a candidate drug for the treatment of depression.

Individuals with cannabis use are associated with widespread morphological alterations in the subregions of the amygdala, hippocampus, and pallidum

BACKGROUND

Cannabis is the most frequently used illicit drug worldwide. Although multiple structural MRI studies of individuals with cannabis use (CB) have been undertaken, the reports of the volume alterations in the amygdala, hippocampus, and pallidum are not consistent. This study aims to detect subregion-level morphological alterations, analyze the correlation areas with cannabis usage characteristics, and gain new insights into the neuro mechanisms of CB.

METHODS

By leveraging the novel surface-based subcortical morphometry method, 20 CB and 22 age- and sex-matched healthy controls (HC) were included to explore their volumetric and morphological differences in the three subcortical structures. Afterward, the correlation analysis between surface morphological eigenvalues and cannabis usage characteristics was performed.

RESULTS

Compared with volumetric measures, the surface-based subcortical morphometry method detected more significant global morphological deformations in the left amygdala, right hippocampus, and right pallidum (overall-p < 0.05, corrected). More obvious morphological alterations (atrophy or expansion) were observed in specific subregions (vertex-based p-value<0.05, uncorrected) of the three subcortical structures. Both positive and negative subregional correlation areas were reported by the correlation analysis.

CONCLUSIONS

The current study illuminated new pathophysiologic mechanisms in the amygdala, hippocampus, and pallidum at the subregion level, which may inform the subsequent smaller-scale CB research.

Multivariate morphometry statistics reveal the morphological change pattern of hippocampus during normal aging

There have been numerous studies focusing on normal aging in previous decades which is accompanied by the structural and functional decline in the hippocampus, while the pattern of hippocampal alteration with age remains unclear. Figuring out the mechanism of hippocampal changes precisely is beneficial for a better understanding of the aging process. In this study, we included a total of 451 T1 MRI scans of subjects of age 50-90 who were labeled as normal in the Alzheimer's Disease Neuroimaging Initiative. Taking 10 years of age as an age band, we divided the subjects into four groups (denoted as HC1, HC2, HC3, and HC4, respectively), with the youngest being 50-60 and the oldest 81-90. Then the Multivariate Morphometry Statistics (MMS) of the hippocampus segmented from the four groups were extracted by surface reconstruction, mesh generation, and surface registration. Finally, the significant differences between the youngest group and the other three were statistically analyzed. Results showed that the earliest deformation region of the left hippocampus located in the frontal subiculum and the dorsal CA1 of the tail part and gradually expanded with aging, while the right hippocampal deformation mainly concentrated in the dorsal CA1 and spread to the posterior CA2-3, which occurred later than that of the left. All the results illustrated that the hippocampus is truly a vulnerable structure in the course of aging, and the MMS are sensitive metrics for detecting the changes in the subcortical convex structure.

Dimorphic evaluation of hippocampal changes in rat model of demyelination: A comparative functional, morphometric, and histological study

BACKGROUND

Multiple sclerosis (MS) is the most common autoimmune disease. Progressive depletion of the brain and spinal cord tissue appears at the onset of the disease. Several studies have shown the increased size of the ventricles of the brain and decreases in the area of the corpus callosum and the width of the brain. Other important symptoms of this disease are cognitive, learning, and memory disorders.

AIM

The aim of this study was to compare morphometric, histological, and functional changes in the demyelination model in both sexes.

MATERIALS AND METHODS

In this experimental study, male and female Wistar rats were studied in four experimental groups. Demyelination was induced by the injection of ethidium bromide in the ventricular region. The chronic effect of demyelination on spatial memory, movement, and coordination was investigated using the Morris Water Maze (MWM), and clinical and balance beam tests, respectively. Myelin degradation, cell death and neurogenesis were estimated using Luxol Fast Blue staining and immunohistochemistry (Caspase-3 and Nestin markers). In addition, morphometric findings were recorded for the brain and hippocampus (weight, volume, length, width).

RESULT

Demyelination increased the time and distance index and decreased the residence time in the target quarter in the water maze test (p < .001). It also increases the neuromuscular and modified neurological severity score (p < .01). Demyelination increases caspase-3 (p < .05) expression and decreases Nestin expression (p < .001), which are directly related to the extent of damage.

CONCLUSION

This study showed an interaction between hippocampal structural and functional networks in explaining spatial learning and memory in the early stages of MS.

Temporal Grading Index of Functional Network Topology Predicts Pain Perception of Patients With Chronic Back Pain

Chronic back pain (CBP) is a maladaptive health problem affecting the brain function and behavior of the patient. Accumulating evidence has shown that CBP may alter the organization of functional brain networks; however, whether the severity of CBP is associated with changes in dynamics of functional network topology remains unclear. Here, we generated dynamic functional networks based on resting-state functional magnetic resonance imaging (rs-fMRI) of 34 patients with CBP and 34 age-matched healthy controls (HC) in the OpenPain database via a sliding window approach, and extracted nodal degree, clustering coefficient (CC), and participation coefficient (PC) of all windows as features to characterize changes of network topology at temporal scale. A novel feature, named temporal grading index (TGI), was proposed to quantify the temporal deviation of each network property of a patient with CBP to the normal oscillation of the HCs. The TGI of the three features achieved outstanding performance in predicting pain intensity on three commonly used regression models (i.e., SVR, Lasso, and elastic net) through a 5-fold cross-validation strategy, with the minimum mean square error of 0.25 ± 0.05; and the TGI was not related to depression symptoms of the patients. Furthermore, compared to the HCs, brain regions that contributed most to prediction showed significantly higher CC and lower PC across time windows in the CBP cohort. These results highlighted spatiotemporal changes in functional network topology in patients with CBP, which might serve as a valuable biomarker for assessing the sensation of pain in the brain and may facilitate the development of CBP management/therapy approaches.

Morphological Biomarkers in the Amygdala and Hippocampus of Children and Adults at High Familial Risk for Depression

Major Depressive Disorder (MDD) is highly familial, and the hippocampus and amygdala are important in the pathophysiology of MDD. Whether morphological markers of risk for familial depression are present in the hippocampus or amygdala is unknown. We imaged the brains of 148 individuals, aged 6 to 54 years, who were members of a three-generation family cohort study and who were at either high or low familial risk for MDD. We compared surface morphological features of the hippocampus and amygdala across risk groups and assessed their associations with depression severity. High- compared with low-risk individuals had inward deformations of the head of both hippocampi and the medial surface of the left amygdala. The hippocampus findings persisted in analyses that included only those participants who had never had MDD, suggesting that these are true endophenotypic biomarkers for familial MDD. Posterior extension of the inward deformations was associated with more severe depressive symptoms, suggesting that a greater spatial extent of this biomarker may contribute to the transition from risk to the overt expression of symptoms. Significant associations of these biomarkers with corresponding biomarkers for cortical thickness suggest that these markers are components of a distributed cortico-limbic network of familial vulnerability to MDD.

Using graph convolutional network to characterize individuals with major depressive disorder across multiple imaging sites

BACKGROUND

Establishing objective and quantitative neuroimaging biomarkers at individual level can assist in early and accurate diagnosis of major depressive disorder (MDD). However, most previous studies using machine learning to identify MDD were based on small sample size and did not account for the brain connectome that is associated with the pathophysiology of MDD. Here, we addressed these limitations by applying graph convolutional network (GCN) in a large multi-site MDD dataset.

METHODS

Resting-state functional MRI scans of 1586 participants (821 MDD vs. 765 controls) across 16 sites of Rest-meta-MDD consortium were collected. GCN model was trained with individual whole-brain functional network to identify MDD patients from controls, characterize the most salient regions contributing to classification, and explore the relationship between topological characteristics of salient regions and clinical measures.

FINDINGS

GCN achieved an accuracy of 81·5% (95%CI: 80·5-82·5%, AUC: 0·865), which was higher than other common machine learning classifiers. The most salient regions contributing to classification were primarily identified within the default mode, fronto-parietal, and cingulo-opercular networks. Nodal topologies of the left inferior parietal lobule and left dorsolateral prefrontal cortex were associated with depressive severity and illness duration, respectively.

INTERPRETATION

These findings based on a large, multi-site dataset support the feasibility and effectiveness of GCN in characterizing MDD, and also illustrate the potential utility of GCN for enhancing understanding of the neurobiology of MDD by detecting clinically-relevant disruption in functional network topology.

FUNDING

This study was supported by the National Natural Science Foundation of China (Grant Nos. 81621003, 82027808, 81820108018).

The impact of Alzheimer's disease susceptibility loci on lateral ventricular surface morphology in older adults

The enlargement of ventricular volume is a general trend in the elderly, especially in patients with Alzheimer's disease (AD). Multiple susceptibility loci have been reported to have an increased risk for AD and the morphology of brain structures are affected by the variations in the risk loci. Therefore, we hypothesized that genes contributed significantly to the ventricular surface, and the changes of ventricular surface were associated with the impairment of cognitive functions. After the quality controls (QC) and genotyping, a lateral ventricular segmentation method was employed to obtain the surface features of lateral ventricle. We evaluated the influence of 18 selected AD susceptibility loci on both volume and surface morphology across 410 subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI). Correlations were conducted between radial distance (RD) and Montreal Cognitive Assessment (MoCA) subscales. Only the C allele at the rs744373 loci in BIN1 gene significantly accelerated the atrophy of lateral ventricle, including the anterior horn, body, and temporal horn of left lateral ventricle. No significant effect on lateral ventricle was found at other loci. Our results revealed that most regions of the bilateral ventricular surface were significantly negatively correlated with cognitive scores, particularly in delayed recall. Besides, small areas of surface were negatively correlated with language, orientation, and visuospatial scores. Together, our results indicated that the genetic variation affected the localized areas of lateral ventricular surface, and supported that lateral ventricle was an important brain structure associated with cognition in the elderly.

Total Triterpenes of Wolfiporia cocos (Schwein.) Ryvarden & Gilb Exerts Antidepressant-Like Effects in a Chronic Unpredictable Mild Stress Rat Model and Regulates the Levels of Neurotransmitters, HPA Axis and NLRP3 Pathway

Purpose:Wolfiporia cocos is frequently used in traditional Chinese medicine to treat depression. However, antidepressant-like effects of the main active ingredients of Wolfiporia cocos, total triterpenes of Wolfiporia cocos (TTWC), are not well studied. This study aimed to investigate those effects and explore their specific mechanisms of action in depth.

Methods: Chemical components of TTWC were analyzed using LC-MS. Depression-like behavior in rats were induced by chronic unpredictable mild stress (CUMS). The suppressive effects of TTWC (60, 120, 240 mg/kg) against CUMS-induced depression-like behavior were evaluated using the forced swimming test (FST), open field test (OFT) and sucrose preference test (SPT). Levels of 5-hydroxytryptamine (5-HT), glutamate (GLU), corticotropin-releasing hormone (CRH), interleukin-1 beta (IL-1beta), interleukin-18 (IL-18), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-alpha) in different groups were determined by ELISA. Western blotting (WB) was used to detect the expression of NLRP3, ASC, pro-caspase-1, caspase-1, pro-IL-1beta, IL-1beta, pro-IL-18, and IL-18 in the prefrontal cortex. Additionally, the mRNA levels of NLRP3, ASC, caspase-1, IL-1beta and IL-18 were detected by RT-PCR.

Results: A total of 69 lanostane-type triterpene acids of TTWC were identified. The results showed that TTWC exhibited an antidepressant-like effect in CUMS rats, reversed the decreased sugar preference in the SPT, reduction of immobility time in the FST, reduced the rest time, increased the total moving distance in the OFT. TTWC increased 5-HT levels and decreased GLU levels in the hippocampus. Moreover, TTWC decreased CRH levels in serum, indicating the regulation of over-activation of the hypothalamic-pituitary-adrenal (HPA) axis. In addition, reduced serum levels of IL-1beta, IL-18, IL-6, and TNF-alpha. The WB results implied that TTWC inhibited the expression of NLRP3, ASC, caspase-1, IL-1beta, and IL-18 in the prefrontal cortex and enhanced the expression of pro-caspase-1, pro-IL-1beta, and pro-IL-18. Although most of the results were not significant, PCR results showed that TTWC inhibited the expression of NLRP3, ASC, caspase-1, IL-1beta, and IL-18 in the prefrontal cortex.

Conclusion: TTWC treatment exerted an antidepressant-like effect and regulates neurotransmitters, HPA axis and NLRP3 signaling pathway. These results indicated the potential of TTWC in preventing the development of depression.

Early Life Stress and Brain Plasticity: From Alterations of Brain Morphology to Development of Psychopathology

Advances in our understanding of the genetics of mental disorders (MD) have contributed to a better understanding of their pathophysiology. Nonetheless, several questions and doubts remain. Recent research has focused on the role of the environment in developing mental disorders, and the advent of neuroscientific methodologies has opened up new avenues of inquiry. However, the mechanism by which childhood stress affects neurodevelopment via mechanisms, such as gene-environment interactions and epigenetic regulation leading to diseases in adulthood, is unclear. This paper aims to review the evidence on the role of early life stress and parental psychopathology in the pathophysiology and clinical expression of MD. Methodology: The study will conduct a comprehensive systematic review using medical search terms (MeSH). Electronic searches for published studies will be performed using the MEDLINE (PubMed), EMBASE, Scopus, PsychINFO, Web of Science, and Google Scholar databases. We will look for research on the neuroplasticity effects of early life stress on development and review articles that evaluate cognitive functions and the development of psychopathology and MD. Before identifying full-text articles, several studies will be filtered based on titles, abstracts, keywords, and synonyms. Publications to be included in the review will be assessed for quality and consistency before inclusion. Data will be extracted independently and duplicated by two authors from each eligible study to ensure consistency between reviews. All databases will be searched from inception until July 2021 and will be limited to human studies. The search will be limited only to publication in the English language and any publication that can be converted to English. Discussion and Conclusions: The findings of this review will meticulously articulate the effects of childhood adversity, such as ELS and parental psychopathology on cognitive development and neuroplasticity. Prospero Registration: CRD42021278100.

Analysis of Hippocampus Evolution Patterns and Prediction of Conversion in Mild Cognitive Impairment Using Multivariate Morphometry Statistics

Background: Mild cognitive impairment (MCI), which is generally regarded as the prodromal stage of Alzheimer’s disease (AD), is associated with morphological changes in brain structures, particularly the hippocampus. However, the indicators for characterizing the deformation of hippocampus in conventional methods are not precise enough and ignore the evolution information with the course of disease. Objective: The purpose of this study was to investigate the temporal evolution pattern of MCI and predict the conversion of MCI to AD by using the multivariate morphometry statistics (MMS) as fine features. Methods: First, we extracted MMS features from MRI scans of 64 MCI converters (MCIc), 81 MCI patients who remained stable (MCIs), and 90 healthy controls (HC). To make full use of the time information, the dynamic MMS (DMMS) features were defined. Then, the areas with significant differences between pairs of the three groups were analyzed using statistical methods and the atrophy/expansion were identified by comparing the metrics. In parallel, patch selection, sparse coding, dictionary learning and maximum pooling were used for the dimensionality reduction and the ensemble classifier GentleBoost was used to classify MCIc and MCIs. Results: The longitudinal analysis revealed that the atrophy of both MCIc and MCIs mainly distributed in dorsal CA1, then spread to subiculum and other regions gradually, while the atrophy area of MCIc was larger and more significant. And the introduction of longitudinal information promoted the accuracy to 91.76% for conversion prediction. Conclusion: The dynamic information of hippocampus holds a huge potential for understanding the pathology of MCI.

Subcortical volumetric alterations as potential predictors of methylphenidate treatment response in youth with attention-deficit/hyperactivity disorder

BACKGROUND

Patients with attention-deficit/hyperactivity disorder (ADHD) show structural alterations in the subcortical and dopaminergic regions of the brain. Methylphenidate is a first-line treatment for ADHD, and it is known to affect the subcortical and dopaminergic systems. The degree of pretreatment structural alterations in patients with ADHD may be an important factor in predicting methylphenidate treatment outcomes. The present study examined whether pretreatment volumetric alterations in the subcortical and dopaminergic regions predicted treatment response in youth with ADHD.

METHODS

This study included 67 youth with ADHD and 25 healthy controls. Youth with ADHD received 8 weeks of methylphenidate treatment. They completed baseline (pretreatment) T ₁-weighted structural MRI scans and underwent clinical assessments before and after methylphenidate treatment. The healthy controls also completed baseline structural MRI scans. We assessed volumetric alterations using relative volumes (volume of each region of interest/intracranial volume).

RESULTS

Among 67 youth with ADHD, 44 were treatment responders and 23 were nonresponders based on post-treatment scores on the Clinical Global Impression Scale-Improvement. Nonresponders had larger volumes in the bilateral amygdala and right thalamus than responders. Nonresponders also had larger volumes in amygdalar subregions (i.e., the bilateral lateral nucleus and right basal nucleus) and hippocampal subregions (i.e., the right hippocampal head and right molecular layer) relative to responders.

LIMITATIONS

We did not collect post-treatment structural T ₁-weighted images, so volumetric changes related to methylphenidate treatment in youth with ADHD were undetermined.

CONCLUSION

These findings suggest that pretreatment volumetric alterations in subcortical regions may serve as biomarkers for predicting methylphenidate treatment response in youth with ADHD.

Potential structural trait markers of depression in the form of alterations in the structures of subcortical nuclei and structural covariance network properties

It has been proposed recently that major depressive disorder (MDD) could represent an adaptation to conserve energy after the perceived loss of an investment in a vital source, such as group identity, personal assets, or relationships. Energy conserving behaviors associated with MDD may form a persistent marker in brain regions and networks involved in cognition and emotion regulation. In this study, we examined whether subcortical regions and volume-based structural covariance networks (SCNs) have state-independent alterations (trait markers). First-episode drug-naïve currently depressed (cMDD) patients (N = 131), remitted MDD (RD) patients (N = 67), and healthy controls (HCs, N = 235) underwent structural magnetic resonance imaging (MRI). Subcortical gray matter volumes (GMVs) were calculated in FreeSurfer software, and group differences in GMVs and SCN were analyzed. Compared to HCs, major findings were decreased GMVs of left pallidum and pulvinar anterior of thalamus in the cMDD and RD groups, indicative of a trait marker. Relative to HCs, subcortical SCNs of both cMDD and RD patients were found to have reduced small-world-ness and path length, which together may represent a trait-like topological feature of depression. In sum, the left pallidum, left pulvinar anterior of thalamus volumetric alterations may represent trait marker and reduced small-world-ness, path length may represent trait-like topological feature of MDD.

Predicting Tau Accumulation in Cerebral Cortex with Multivariate MRI Morphometry Measurements, Sparse Coding, and Correntropy

Biomarker-assisted diagnosis and intervention in Alzheimer's disease (AD) may be the key to prevention breakthroughs. One of the hallmarks of AD is the accumulation of tau plaques in the human brain. However, current methods to detect tau pathology are either invasive (lumbar puncture) or quite costly and not widely available (Tau PET). In our previous work, structural MRI-based hippocampal multivariate morphometry statistics (MMS) showed superior performance as an effective neurodegenerative biomarker for preclinical AD and Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP) has excellent ability to generate low-dimensional representations with strong statistical power for brain amyloid prediction. In this work, we apply this framework together with ridge regression models to predict Tau deposition in Braak12 and Braak34 brain regions separately. We evaluate our framework on 925 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Each subject has one pair consisting of a PET image and MRI scan which were collected at about the same times. Experimental results suggest that the representations from our MMS and PASCS-MP have stronger predictive power and their predicted Braak12 and Braak34 are closer to the real values compared to the measures derived from other approaches such as hippocampal surface area and volume, and shape morphometry features based on spherical harmonics (SPHARM).

Synergistic Effects of APOE and CLU May Increase the Risk of Alzheimer's Disease: Acceleration of Atrophy in the Volumes and Shapes of the Hippocampus and Amygdala

BACKGROUND

The volume loss of the hippocampus and amygdala in non-demented individuals has been reported to increase the risk of developing Alzheimer's disease (AD). Many neuroimaging genetics studies mainly focused on the individual effects of APOE and CLU on neuroimaging to understand their neural mechanisms, whereas their synergistic effects have been rarely studied.

OBJECTIVE

To assess whether APOE and CLU have synergetic effects, we investigated the epistatic interaction and combined effects of the two genetic variants on morphological degeneration of hippocampus and amygdala in the non-demented elderly at baseline and 2-year follow-up.

METHODS

Besides the widely-used volume indicator, the surface-based morphometry method was also adopted in this study to evaluate shape alterations.

RESULTS

Our results showed a synergistic effect of homozygosity for the CLU risk allele C in rs11136000 and APOEɛ4 on the hippocampal and amygdalar volumes during a 2-year follow-up. Moreover, the combined effects of APOEɛ4 and CLU C were stronger than either of the individual effects in the atrophy progress of the amygdala.

CONCLUSION

These findings indicate that brain morphological changes are caused by more than one gene variant, which may help us to better understand the complex endogenous mechanism of AD.

Gut Hormones as Potential Therapeutic Targets or Biomarkers of Response in Depression: The Case of Motilin

Recent research has identified the gut–brain axis as a key mechanistic pathway and potential therapeutic target in depression. In this paper, the potential role of gut hormones as potential treatments or predictors of response in depression is examined, with specific reference to the peptide hormone motilin. This possibility is explored through two methods: (1) a conceptual review of the possible links between motilin and depression, including evidence from animal and human research as well as clinical trials, based on a literature search of three scientific databases, and (2) an analysis of the relationship between a functional polymorphism (rs2281820) of the motilin (MLN) gene and cross-national variations in the prevalence of depression based on allele frequency data after correction for potential confounders. It was observed that (1) there are several plausible mechanisms, including interactions with diet, monoamine, and neuroendocrine pathways, to suggest that motilin may be relevant to the pathophysiology and treatment of depression, and (2) there was a significant correlation between rs2281820 allele frequencies and the prevalence of depression after correcting for multiple confounding factors. These results suggest that further evaluation of the utility of motilin and related gut peptides as markers of antidepressant response is required and that these molecular pathways represent potential future mechanisms for antidepressant drug development.

Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases

Biomarker assisted preclinical/early detection and intervention in Alzheimer’s disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (Aβ) plaques in the human brain. However, current methods to detect Aβ pathology are either invasive (lumbar puncture) or quite costly and not widely available (amyloid PET). Our prior studies show that magnetic resonance imaging (MRI)-based hippocampal multivariate morphometry statistics (MMS) are an effective neurodegenerative biomarker for preclinical AD. Here we attempt to use MRI-MMS to make inferences regarding brain Aβ burden at the individual subject level. As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse-coding and Max-Pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each individual subject. Then we apply these individual representations and a binary random forest classifier to predict brain Aβ positivity for each person. We test our method in two independent cohorts, 841 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 260 subjects from the Open Access Series of Imaging Studies (OASIS). Experimental results suggest that our proposed PASCS-MP method and MMS can discriminate Aβ positivity in people with mild cognitive impairment (MCI) [Accuracy (ACC) = 0.89 (ADNI)] and in cognitively unimpaired (CU) individuals [ACC = 0.79 (ADNI) and ACC = 0.81 (OASIS)]. These results compare favorably relative to measures derived from traditional algorithms, including hippocampal volume and surface area, shape measures based on spherical harmonics (SPHARM) and our prior Patch Analysis-based Surface Sparse-coding and Max-Pooling (PASS-MP) methods.

Amygdala subnuclei development in adolescents with autism spectrum disorder: Association with social communication and repetitive behaviors

INTRODUCTION

The amygdala subnuclei regulate emotional processing and are widely implicated in social cognitive impairments often seen in children with autism spectrum disorder (ASD). Dysregulated amygdala development has been reported in young children with ASD; less is known about amygdala maturation in later adolescence, a sensitive window for social skill development.

METHODS

The macrostructural development of the amygdala subnuclei was assessed at two time points in a longitudinal magnetic resonance imaging (MRI) study of adolescents with ASD (n = 23) and typically-developing adolescents (n = 15) . In adolescents with ASD, amygdala subnuclei growth was assessed in relation to ASD symptomatology based on standardized diagnostic assessments. Participants were scanned with MRI at median age of 12 years and returned for a second scan at a median age of 15 years. The volumes of nine amygdala subnuclei were extracted using an automatic segmentation algorithm.

RESULTS

When examining the longitudinal data acquired across two time points, adolescents with ASD had larger basolateral amygdala (BLA) nuclei volumes compared to typically developing adolescents (B = 46.8, p = 0.04). When examining ASD symptomatology in relation to the growth of the amygdala subnuclei, reciprocal social interaction scores on the ADI-R were positively associated with increased growth of the BLA nuclei (B = 8.3, p < 0.001). Growth in the medial nucleus negatively predicted the communication (B = -46.9, p = 0.02) and social (B = -47.7, p < 0.001) domains on the ADOS-G. Growth in the right cortical nucleus (B = 26.14, p = 0.02) positively predicted ADOS-G social scores. Central nucleus maturation (B = 29.9, p = 0.02) was associated with the repetitive behaviors domain on the ADOS-G.

CONCLUSIONS

Larger BLA volumes in adolescents with ASD may reflect underlying alterations in cellular density previously reported in post-mortem studies. Furthermore, findings demonstrate an association between regional growth in amygdala subnuclei volumes and ASD symptomatology. Improved understanding of the developmental trajectories of the amygdala subnuclei may aid in identifying key windows for interventions, particularly for social communication, in adolescents with ASD.

Therapeutic potential of ketamine for alcohol use disorder

Excessive alcohol consumption is involved in 1/10 of deaths of U.S. working-age adults and costs the country around $250,000,000 yearly. While Alcohol Use Disorder (AUD) pathology is complex and involves multiple neurotransmitter systems, changes in synaptic plasticity, hippocampal neurogenesis, and neural connectivity have been implicated in the behavioral characteristics of AUD. Depressed mood and stress are major determinants of relapse in AUD, and there is significant comorbidity between AUD, depression, and stress disorders, suggesting potential for overlap in their treatments. Disulfiram, naltrexone, and acamprosate are current pharmacotherapies for AUD, but these treatments have limitations, highlighting the need for novel therapeutics. Ketamine is a N-methyl-D-Aspartate receptor antagonist, historically used in anesthesia, but also affects other neurotransmitters systems, synaptic plasticity, neurogenesis, and neural connectivity. Currently under investigation for treating AUDs and other Substance Use Disorders (SUDs), ketamine has strong support for efficacy in treating clinical depression, recently receiving FDA approval. Ketamine's effect in treating depression and stress disorders, such as PTSD, and preliminary evidence for treating SUDs further suggests a role for treating AUDs. This review explores the behavioral and neural evidence for treating AUDs with ketamine and clinical data on ketamine therapy for AUDs and SUDs.

Chronic intermittent ethanol promotes ventral subiculum hyperexcitability via increases in extrinsic basolateral amygdala input and local network activity

The hippocampus, particularly its ventral domain, can promote negative affective states (i.e. stress and anxiety) that play an integral role in the development and persistence of alcohol use disorder (AUD). The ventral hippocampus (vHC) receives strong excitatory input from the basolateral amygdala (BLA) and the BLA-vHC projection bidirectionally modulates anxiety-like behaviors. However, no studies have examined the effects of chronic alcohol on the BLA-vHC circuit. In the present study, we used ex vivo electrophysiology in conjunction with optogenetic approaches to examine the effects of chronic intermittent ethanol exposure (CIE), a well-established rodent model of AUD, on the BLA-vHC projection and putative intrinsic vHC synaptic plasticity. We discovered prominent BLA innervation in the subicular region of the vHC (vSub). CIE led to an overall increase in the excitatory/inhibitory balance, an increase in AMPA/NMDA ratios but no change in paired-pulse ratios, consistent with a postsynaptic increase in excitability in the BLA-vSub circuit. CIE treatment also led to an increase in intrinsic network excitability in the vSub. Overall, our findings suggest a hyperexcitable state in BLA-vSub specific inputs as well as intrinsic inputs to vSub pyramidal neurons which may contribute to the negative affective behaviors associated with CIE.

Relationship between depression and olfactory sensory function: a review

Links between olfactory sensory function and effect have been well established. A robust literature exists in both humans and animals showing that disrupting olfaction sensory function can elicit disordered mood state, including serve as a model of depression. Despite this, considerably less is known regarding the directionality and neural basis of this relationship, e.g. whether disruptions in sensory function precede and contribute to altered mood or if altered mood state precipitates changes in olfactory perception. Further, the neural basis of altered olfactory function in depression remains unclear. In conjunction with clinical studies, animal models represent a valuable tool to understand the relationship between altered mood and olfactory sensory function. Here, we review the relevant literature assessing olfactory performance in depression in humans and in rodent models of depressive-like behavioral states. Rodents allow for detailed characterization of alterations in olfactory perception, manipulation of experiential events that elicit depressive-like phenotypes, and allow for interrogation of potential predictive markers of disease and the cellular basis of olfactory impairments associated with depressive-like phenotypes. We synthesize these findings to identify paths forward to investigate and understand the complex interplay between depression and olfactory sensory function.

Brain Functional Networks Based on Resting-State EEG Data for Major Depressive Disorder Analysis and Classification

If the brain is regarded as a system, it will be one of the most complex systems in the universe. Traditional analysis and classification methods of major depressive disorder (MDD) based on electroencephalography (EEG) feature-levels often regard electrode as isolated node and ignore the correlation between them, so it's difficult to find alters of abnormal topological architecture in brain. To solve this problem, we propose a brain functional network framework for MDD of analysis and classification based on resting state EEG. The phase lag index (PLI) was calculated based on the 64-channel resting state EEG to construct the function connection matrix to reduce and avoid the volume conductor effect. Then binarization of brain function network based on small world index was realized. Statistical analyses were performed on different EEG frequency band and different brain regions. The results showed that significant alterations of brain synchronization occurred in frontal, temporal, parietal-occipital regions of left brain and temporal region of right brain. And average shortest path length and clustering coefficient in left central region of theta band and node betweenness centrality in right parietal-occipital region were significantly correlated with PHQ-9 score of MDD, which indicates these three network metrics may be served as potential biomarkers to effectively distinguish MDD from controls and the highest classification accuracy can reach 93.31%. Our findings also point out that the brain function network of MDD patients shows a random trend, and small world characteristics appears to weaken.

Hippocampal and Amygdalar Volume Changes in Major Depressive Disorder: A Targeted Review and Focus on Stress

Medial temporal lobe structures have long been implicated in the pathogenesis of major depressive disorder. Although findings of smaller hippocampal and amygdalar volumes are common, inconsistencies remain in the literature. In this targeted review, we examine recent and significant neuroimaging papers examining the volumes of these structures in major depressive disorder. A targeted PubMed/Google Scholar search was undertaken focusing on volumetric neuroimaging studies of the hippocampus and amygdala in major depressive disorder. Where possible, mean volumes and accompanying standard deviations were extracted allowing computation of Cohen’s d_s effect sizes. Although not a meta-analysis, this allows a broad comparison of volume changes across studies. Thirty-nine studies in total were assessed. Hippocampal substructures and amygdale substructures were investigated in 11 and 2 studies, respectively. The hippocampus was more consistently smaller than the amygdala across studies, which is reflected in the larger cumulative difference in volume found with the Cohen’s d_s calculations. The left and right hippocampi were, respectively, 92% and 91.3% of the volume found in controls, and the left and right amygdalae were, respectively, 94.8% and 92.6% of the volume of controls across all included studies. The role of stress in temporal lobe structure volume reduction in major depressive disorder is discussed.

Applying surface-based morphometry to study ventricular abnormalities of cognitively unimpaired subjects prior to clinically significant memory decline

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A completely automated surface-based ventricular morphometry system.

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Generate a whole connected 3D ventricular shape model.

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Test-retest the system in two independent CU subject cohorts.

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Subregional ventricular abnormalities prior to clinically memory decline.

Ventricular volume (VV) is a widely used structural magnetic resonance imaging (MRI) biomarker in Alzheimer’s disease (AD) research. Abnormal enlargements of VV can be detected before clinically significant memory decline. However, VV does not pinpoint the details of subregional ventricular expansions. Here we introduce a ventricular morphometry analysis system (VMAS) that generates a whole connected 3D ventricular shape model and encodes a great deal of ventricular surface deformation information that is inaccessible by VV. VMAS contains an automated segmentation approach and surface-based multivariate morphometry statistics. We applied VMAS to two independent datasets of cognitively unimpaired (CU) groups. To our knowledge, it is the first work to detect ventricular abnormalities that distinguish normal aging subjects from those who imminently progress to clinically significant memory decline. Significant bilateral ventricular morphometric differences were first shown in 38 members of the Arizona APOE cohort, which included 18 CU participants subsequently progressing to the clinically significant memory decline within 2 years after baseline visits (progressors), and 20 matched CU participants with at least 4 years of post-baseline cognitive stability (non-progressors). VMAS also detected significant differences in bilateral ventricular morphometry in 44 Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects (18 CU progressors vs. 26 CU non-progressors) with the same inclusion criterion. Experimental results demonstrated that the ventricular anterior horn regions were affected bilaterally in CU progressors, and more so on the left. VMAS may track disease progression at subregional levels and measure the effects of pharmacological intervention at a preclinical stage.

Ghrelin exhibited antidepressant and anxiolytic effect via the p38-MAPK signaling pathway in hippocampus

Ghrelin, a peptide derived from stomach, is an endogenous ligand for growth hormone secretagogue receptor (GHSR). So far, the exact role of ghrelin in depression and anxiety is still being debated. The p38 mitogen-activated protein kinase (p38-MAPK) is known to be activated in response to various stress stimuli. Thus, we hypothesize that ghrelin has an antidepressant effect, to which the p38-MAPK signaling pathway significantly contributes. To test this hypothesis, chronic social defeat stress (CSDS) was used as a model of depression. We employed the adeno-associated virus-mediated siRNA approach to down-regulate GHSR expression in the hippocampus of mice in vivo. Both ghrelin and the p38 inhibitor, SB203580, were administered to identify the effect of ghrelin on depressive-like behavior of stressed mice and to better assess the role of the p38-MAPK signaling pathway in this process. We found that CSDS activated the endogenous ghrelin-GHSR in hippocampal neurons, which possibly resulted in opposing the formation of depression- and anxiety-like behaviors in mice. Furthermore, the p38-MAPK signaling pathway had an important role in the antidepressant effect of ghrelin. Therefore, we conclude that ghrelin may reduce CSDS-induced depression- and anxiety-like behaviors via inhibiting the p38-MAPK signaling pathway in hippocampal neurons of mice.

Applying surface-based hippocampal morphometry to study APOE-E4 allele dose effects in cognitively unimpaired subjects

Apolipoprotein E (APOE) e4 is the major genetic risk factor for late-onset Alzheimer's disease (AD). The dose-dependent impact of this allele on hippocampal volumes has been documented, but its influence on general hippocampal morphology in cognitively unimpaired individuals is still elusive. Capitalizing on the study of a large number of cognitively unimpaired late middle aged and older adults with two, one and no APOE-e4 alleles, the current study aims to characterize the ability of our automated surface-based hippocampal morphometry algorithm to distinguish between these three levels of genetic risk for AD and demonstrate its superiority to a commonly used hippocampal volume measurement. We examined the APOE-e4 dose effect on cross-sectional hippocampal morphology analysis in a magnetic resonance imaging (MRI) database of 117 cognitively unimpaired subjects aged between 50 and 85 years (mean = 57.4, SD = 6.3), including 36 heterozygotes (e3/e4), 37 homozygotes (e4/e4) and 44 non-carriers (e3/e3). The proposed automated framework includes hippocampal surface segmentation and reconstruction, higher-order hippocampal surface correspondence computation, and hippocampal surface deformation analysis with multivariate statistics. In our experiments, the surface-based method identified APOE-e4 dose effects on the left hippocampal morphology. Compared to the widely-used hippocampal volume measure, our hippocampal morphometry statistics showed greater statistical power by distinguishing cognitively unimpaired subjects with two, one, and no APOE-e4 alleles. Our findings mirrored previous studies showing that APOE-e4 has a dose effect on the acceleration of brain structure deformities. The results indicated that the proposed surface-based hippocampal morphometry measure is a potential preclinical AD imaging biomarker for cognitively unimpaired individuals.

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Applied surface-based hippocampal morphometry on cognitively unimpaired subjects.

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Our study identified APOE-e4 dose effects on cognitively unimpaired subjects.

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Surface-based hippocampal morphometry outperformed the hippocampal volume measure.

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Surface-based hippocampal morphometry may be a potential preclinical AD biomarker.