Abnormalities In Major Depressive Disorder Research Articles

Acute Stress Increases Striatal Connectivity With Cortical Regions Enriched for μ and κ Opioid Receptors

BackgroundUnderstanding the neurobiological effects of stress is critical for addressing the etiology of major depressive disorder (MDD). Using a dimensional approach involving individuals with differing degree of MDD risk, we investigated 1) the effects of acute stress on cortico-cortical and subcortical-cortical functional connectivity (FC) and 2) how such effects are related to gene expression and receptor maps. MethodsAcross 115 participants (37 control, 39 remitted MDD, 39 current MDD), we evaluated the effects of stress on FC during the Montreal Imaging Stress Task. Using partial least squares regression, we investigated genes whose expression in the Allen Human Brain Atlas was associated with anatomical patterns of stress-related FC change. Finally, we correlated stress-related FC change maps with opioid and GABAA (gamma-aminobutyric acid A) receptor distribution maps derived from positron emission tomography. ResultsResults revealed robust effects of stress on global cortical connectivity, with increased global FC in frontoparietal and attentional networks and decreased global FC in the medial default mode network. Moreover, robust increases emerged in FC of the caudate, putamen, and amygdala with regions from the ventral attention/salience network, frontoparietal network, and motor networks. Such regions showed preferential expression of genes involved in cell-to-cell signaling (OPRM1, OPRK1, SST, GABRA3, GABRA5), similar to previous genetic MDD studies. ConclusionsAcute stress altered global cortical connectivity and increased striatal connectivity with cortical regions that express genes that have previously been associated with imaging abnormalities in MDD and are rich in μ and κ opioid receptors. These findings point to overlapping circuitry underlying stress response, reward, and MDD.

Changes of structural functional connectivity coupling and its correlations with cognitive function in patients with major depressive disorder

BackgroundPrevious neuroimaging studies have reported structural and functional brain abnormalities in major depressive disorder (MDD). This study aimed to explore whether the coherence of structural-functional networks was affected by disease and investigate its correlation with clinical manifestations. MethodsThe severity of symptoms and cognitive function of 121 MDD patients and 139 healthy controls (HC) were assessed, and imaging data, including diffusion tensor imaging, T1 structural magnetic resonance imaging (MRI) and resting-state functional MRI, were collected. Spearman correlation coefficients of Kullback–Leibler similarity (KLS), fiber number (FN), fractional anisotropy (FA) and functional connectivity (FC) were calculated as coupling coefficients. Double-weight median correlation analysis was conducted to investigate the correlations between differences in brain networks and clinical assessments. ResultsThe percentage of total correct response of delayed matching to sample and the percentage of delayed correct response of pattern recognition memory was lower in MDD. Compared with the HC, KLS-FC coupling between the parietal lobe and subcortical area, FA-FC coupling between the temporal and parietal lobe, and FN-FC coupling in the frontal lobe was lower in MDD. Several correlations between structural-functional connectivity and clinical manifestations were identified. LimitationsFirst, our study lacks longitudinal follow-up data. Second, the sample size was relatively small. Moreover, we only used the Anatomical Automatic Labeling template to construct the brain network. Finally, the validation of the causal relationship of neuroimaging-behavior factors was still insufficient. ConclusionsThe alternation in structural-functional coupling were related to clinical characterization and might be involved in the neuropathology of depression.

Integrative omics analysis reveals epigenomic and transcriptomic signatures underlying brain structural deficits in major depressive disorder

Several lines of evidence support the involvement of transcriptomic and epigenetic mechanisms in the brain structural deficits of major depressive disorder (MDD) separately. However, research in these two areas has remained isolated. In this study, we proposed an integrative strategy that combined neuroimaging, brain-wide gene expression, and peripheral DNA methylation data to investigate the genetic basis of gray matter abnormalities in MDD. The MRI T1-weighted images and Illumina 850 K DNA methylation microarrays were obtained from 269 patients and 416 healthy controls, and brain-wide transcriptomic data were collected from Allen Human Brain Atlas. The between-group differences in gray matter volume (GMV) and differentially methylated CpG positions (DMPs) were examined. The genes with their expression patterns spatially related to GMV changes and genes with DMPs were overlapped and selected. Using principal component regression, the associations between DMPs in overlapped genes and GMV across individual patients were investigated, and the region-specific correlations between methylation status and gene expression were examined. We found significant associations between the decreased GMV and DMPs methylation status in the anterior cingulate cortex, inferior frontal cortex, and fusiform face cortex regions. These DMPs genes were primarily enriched in the neurodevelopmental and synaptic transmission process. There was a significant negative correlation between DNA methylation and gene expression in genes associated with GMV changes of the frontal cortex in MDD. Our findings suggest that GMV abnormalities in MDD may have a transcriptomic and epigenetic basis. This imaging-transcriptomic-epigenetic integrative analysis provides spatial and biological links between cortical morphological deficits and peripheral epigenetic signatures in MDD.

Compressed primary-to-transmodal gradient is accompanied with subcortical alterations and linked to neurotransmitters and cellular signatures in major depressive disorder.

Major depressive disorder (MDD) has been shown to involve widespread changes in low-level sensorimotor and higher-level cognitive functions. Recent research found that a primary-to-transmodal gradient could capture a cortical hierarchical organization ranging from perception and action to cognition in healthy subjects, but a prominent gradient dysfunction in MDD patients. However, whether and how this cortical gradient is linked to subcortical impairments and whether it is reflected in the microscale neurotransmitter systems and cell type-specific transcriptional signatures remain largely unknown. Data were acquired from 323 MDD patients and 328 sex- and age-matched healthy controls derived from the REST-meta-MDD project, and the human brain neurotransmitter systems density maps and gene expression data were drawn from two publicly available datasets. We investigated alterations of the primary-to-transmodal gradient in MDD patients and their correlations with clinical symptoms of depression and anxiety, as well as their paralleled subcortical impairments. The correlations between MDD-related gradient alterations and densities of the neurotransmitter systems and gene expression information were assessed, respectively. The results demonstrated that MDD patients had a compressed primary-to-transmodal gradient accompanied by paralleled alterations in subcortical regions including the caudate, amygdala, and thalamus. The case-control gradient differences were spatially correlated with the densities of the neurotransmitter systems including the serotonin and dopamine receptors, and meanwhile with gene expression enriched in astrocytes, excitatory and inhibitory neuronal cells. These findingsmapped the paralleled subcortical impairments in cortical hierarchical organization and also helped us understand the possible molecular and cellular substrates of the co-occurrence of high-level cognitive impairments with low-level sensorimotor abnormalities in MDD.

Network Analysis of Behavioral Activation/Inhibition Systems and Brain Volume in Individuals With and Without Major Depressive Disorder or Social Anxiety Disorder

BackgroundSocial anxiety disorder (SAD) and major depressive disorder (MDD) are characterized by behavioral abnormalities in motivational systems, namely the behavioral inhibition system (BIS) and behavioral activation system (BAS). Limited studies indicate brain volume in regions that support emotion, learning/memory, reward, and cognitive functions relate to BIS/BAS. To increase understanding of BIS/BAS, the current study used a network approach. MethodsPatients with SAD (n = 59), patients with MDD (n = 64), and healthy control participants (n = 36) completed a BIS/BAS questionnaire and structural magnetic resonance imaging scans; volumetric regions of interest comprised cortical and limbic structures based on previous BIS/BAS studies. A Bayesian Gaussian graphical model was used for each diagnostic group, and groups were compared. Among network metrics, bridge centrality was of primary interest. Analysis of variance evaluated BIS/BAS behaviors between groups. ResultsBridge centrality showed hippocampus positively related to BAS, but not to BIS, in the MDD group; no findings were observed in the SAD or control groups. Yet, network density (i.e., overall strength of relationships between variables) and degree centrality (i.e., overall relationship between one variable to all other variables) showed that cortical (e.g., precuneus, medial orbitofrontal) and subcortical (e.g., amygdala, hippocampus) regions differed between diagnostic groups. Analysis of variance results showed BAS was lower in the MDD/SAD groups compared with the control group, while BIS was higher in the SAD group relative to the MDD group, which in turn was higher than the control group. ConclusionsPreliminary findings indicate that network-level aberrations may underlie motivational abnormalities in MDD and SAD. Evidence of BIS/BAS differences builds on previous work that points to shared and distinct motivational differences in internalizing psychopathologies.

Childhood trauma and social support affect symptom profiles through cortical thickness abnormalities in major depressive disorder: A structural equation modeling analysis

BackgroundChildhood trauma, low social support, and alexithymia are recognized as risk factors for major depressive disorder (MDD). However, the mechanisms of risk factors, symptoms, and corresponding structural brain abnormalities in MDD are not fully understood. Structural equation modeling (SEM) has advantages in studying multivariate interrelationships. We aim to illustrate their relationships using SEM. Methods313 MDD patients (213 female; mean age 42.49 years) underwent magnetic resonance imaging and completed assessments. We integrated childhood trauma, alexithymia, social support, anhedonia, depression, anxiety, suicidal ideation and cortical thickness into a multivariate SEM. ResultsWe first established the risk factors-clinical phenotype SEM with an adequate fit. Cortical thickness results show a negative correlation of childhood trauma with the left middle temporal gyrus (MTG) (p = 0.012), and social support was negatively correlated with the left posterior cingulate cortex (PCC) (p < 0.001). The final good fit SEM (χ2 = 32.92, df = 21, χ2/df = 1.57, CFI = 0.962, GFI = 0.978, RMSEA = 0.043) suggested two pathways, with left PCC thickness mediating the relationship between social support and suicidal ideation, and left MTG thickness mediating between childhood trauma and anhedonia/anxiety. ConclusionOur findings provide evidence for the impact of risk factor variables on the brain structure and clinical phenotype of MDD patients. Insufficient social support and childhood trauma might lead to corresponding cortical abnormalities in PCC and MTG, affecting the patient’s mood and suicidal ideation. Future interventions should aim at these nodes.

White matter microstructure changes in adults with major depressive disorder: evidence from diffusion magnetic resonance imaging

Major depressive disorder (MDD) is a serious psychiatric disorder marked by low mood and anhedonia. Understanding the neural mechanism of MDD is essential for the treatment of depression. White matter fibres, connecting different computational units in the brain, have an important effect on brain function; however, the mechanism of white matter fibre abnormality in MDD is still unclear. Our study expected to find white matter abnormalities associated with the frontal lobe and hippocampus in individuals with MDD. Using diffusion tensor imaging data and tract-based spatial statistics, we investigated the microstructural differences in white matter fibre tracts between 30 adults with MDD compared with 31 healthy controls, and calculated the association between MDD-related microstructural changes and illness duration. It was found that patients with MDD showed reduced fractional anisotropy in the genu and body of the corpus callosum, right corona radiata and part of the thalamic radiations, suggesting lower fibrous myelination levels in these regions; the decreased fractional anisotropy in these regions was associated with longer illness duration. Our results suggest that MDD may be associated with microstructural damage of key fibre tracts, which could provide insights into the understanding and treatment of MDD.

A Comprehensive Overview of the Role of Visual Cortex Malfunction in Depressive Disorders: Opportunities and Challenges.

Major depressive disorder (MDD) is a highly heterogeneous mental disorder, and its complex etiology and unclear mechanism are great obstacles to the diagnosis and treatment of the disease. Studies have shown that abnormal functions of the visual cortex have been reported in MDD patients, and the actions of several antidepressants coincide with improvements in the structure and synaptic functions of the visual cortex. In this review, we critically evaluate current evidence showing the involvement of the malfunctioning visual cortex in the pathophysiology and therapeutic process of depression. In addition, we discuss the molecular mechanisms of visual cortex dysfunction that may underlie the pathogenesis of MDD. Although the precise roles of visual cortex abnormalities in MDD remain uncertain, this undervalued brain region may become a novel area for the treatment of depressed patients.

Gene Expression has Distinct Associations with Brain Structure and Function in Major Depressive Disorder.

Major depressive disorder (MDD) is associated with structural and functional brain abnormalities. MDD as well as brain anatomy and function are influenced by genetic factors, but the role of gene expression remains unclear. Here, this work investigates how cortical gene expression contributes to structural and functional brain abnormalities in MDD. This work compares the gray matter volume and resting-state functional measures in a Chinese sample of 848 MDD patients and 749 healthy controls, and these case-control differences are then associated with cortical variation of gene expression. While whole gene expression is positively associated with structural abnormalities, it is negatively associated with functional abnormalities. This work observes the relationships of expression levels with brain abnormalities for individual genes, and found that transcriptional correlates of brain structure and function show opposite relations with gene dysregulation in postmortem cortical tissue from MDD patients. This work further identifies genes that are positively or negatively related to structural abnormalities as well as functional abnormalities. The MDD-related genes are enriched for brain tissue, cortical cells, and biological pathways. These findings suggest that distinct genetic mechanisms underlie structural and functional brain abnormalities in MDD, and highlight the importance of cortical gene expression for the development of cortical abnormalities.

Cerebral blood flow changes and their genetic mechanisms in major depressive disorder: a combined neuroimaging and transcriptome study.

Extensive research has shown abnormal cerebral blood flow (CBF) in patients with major depressive disorder (MDD) that is a heritable disease. The objective of this study was to investigate the genetic mechanisms of CBF abnormalities in MDD. To achieve a more thorough characterization of CBF changes in MDD, we performed a comprehensive neuroimaging meta-analysis of previous literature as well as examined group CBF differences in an independent sample of 133 MDD patients and 133 controls. In combination with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were conducted to identify genes whose expression correlated with CBF changes in MDD, followed by a set of gene functional feature analyses. We found increased CBF in the reward circuitry and default-mode network and decreased CBF in the visual system in MDD patients. Moreover, these CBF changes were spatially associated with expression of 1532 genes, which were enriched for important molecular functions, biological processes, and cellular components of the cerebral cortex as well as several common mental disorders. Concurrently, these genes were specifically expressed in the brain tissue, in immune cells and neurons, and during nearly all developmental stages. Regarding behavioral relevance, these genes were associated with domains involving emotion and sensation. In addition, these genes could construct a protein-protein interaction network supported by 60 putative hub genes with functional significance. Our findings suggest a cerebral perfusion redistribution in MDD, which may be a consequence of complex interactions of a wide range of genes with diverse functional features.

Connectivity model of the anatomic substrates and network abnormalities in major depressive disorder: A coordinate meta-analysis of resting-state functional connectivity

Increasing data suggests major depressive disorder (MDD) involves abnormal functional connectivity within a variety of large-scale brain networks. However, due to the use of unstandardized parcellation schemes, the interactions between these networks and the specific neuroanatomic substrates involved requires further review. We therefore sought to conduct a meta-analysis of functional connectivity changes encountered in MDD using a detailed and standardized parcellation scheme. A literature search for relevant resting-state fMRI studies related to MDD in PubMed was conducted. BrainMap's GingerALE 2.3.6 extracted the relevant fMRI data for creation of an activation likelihood estimation (ALE). A sphere was placed at the MNI coordinate of each ALE cluster and seed origin point, and the Human Connectome Project (HCP) parcellation schema was projected on these spheres. The parcellations most present in the ALE were analyzed based on their associated functional network and/or subcortical area to identify abnormal pairs based on the ALE and seed origin parcellation. Ultimately, 483 subjects across 15 studies were analyzed, wherein areas of decreased or increased functional connectivity compared to healthy controls were identified. Our MDD model most commonly implicated increased default mode network (DMN)-central executive network (CEN) pairs, while decreased paired networks commonly included the DMN with other brain networks. All intra DMN-DMN connections and salience network (SN) pairs showed decreased functional connectivity, while all intra CEN-CEN functional connectivity were increased compared to controls. We hypothesize that our findings of abnormal connectivity between the DMN, CEN, and SN core cognitive networks may demonstrate the inappropriate allocation of cognitive resources and cognitive depletion believed to cause persisting rumination in depression. Despite previous claims, DMN connectivity was found to be generally decreased, and we propose its connectivity direction is dependent on its interacting network partner and the specific parcellations involved. While both of these hypotheses remain speculative and require further validation, our work provides a comprehensive and anatomically precise model to be refined in future studies focusing on the functional connectivity underlying MDD pathophysiology.

Major depression and the biological hallmarks of aging.

Major depressive disorder (MDD) is characterized by psychological and physiological manifestations contributing to the disease severity and outcome. In recent years, several lines of evidence have suggested that individuals with MDD have an elevated risk of age-related adverse outcomes across the lifespan. This review provided evidence of a significant overlap between the biological abnormalities in MDD and biological changes commonly observed during the aging process (i.e., hallmarks of biological aging). Based on such evidence, we formulate a mechanistic model showing how abnormalities in the hallmarks of biological aging can be a common denominator and mediate the elevated risk of age-related health outcomes commonly observed in MDD. Finally, we proposed a roadmap for novel studies to investigate the intersection between the biology of aging and MDD, including the use of geroscience-guided interventions, such as senolytics, to delay or improve major depression by targeting biological aging.

Memory and processing speed impairments in first-episode drug-naïve patients with major depressive disorder

BackgroundCognitive impairment, an intrinsic feature of major depressive disorder (MDD), affects daily and social functioning in depression patients. However, the cognitive impairment profile in MDD remains ambiguous because of the high heterogeneity of previous studies. MethodsFour cognitive domains, including memory, processing speed, executive function (EF), and attention, were assessed in 184 first-episode drug-naïve (FEDN) MDD patients and matched 71 healthy controls (HCs). The effects of demographic and depressive factors on cognitive performance were analyzed using various statistical methods, including multi-factor analysis of variance, Mann-Whitney U test, and Spearman's rank correlation. In addition, the impact of depression severity on cognitive function was further assessed using subgroup analyses and partial correlation analyses. ResultsAge and education significantly impacted most cognitive performances, and depression severity appeared to influence processing speed. Moreover, cognitive scores in memory and processing speed, rather than in EF and attention, were significantly different between FEDN MDD patients and HCs after controlling for sex, age, educational attainment, household income, and body mass index. LimitationsThe number of HCs was relatively small, which may have slightly reduced the study's statistical power. ConclusionsAge and educational attainment have confirmative confounding effects greater than those of depression in most cognitive functions. More importantly, memory and processing speed were impaired in MDD after strictly controlling for confounders. These findings provide new information for understanding the pattern of cognitive impairment and offer clues for further exploring the pathogenesis of cognitive abnormalities in MDD.

Increased Aperiodic Neural Activity During Sleep in Major Depressive Disorder

BackgroundIn major depressive disorder (MDD), patients often express subjective sleep complaints, while polysomnographic studies report only subtle alterations of the electroencephalographic signal. We hypothesize that differentiating the signal into its oscillatory and aperiodic components may bring new insights into our understanding of sleep abnormalities in MDD. Specifically, we investigated aperiodic neural activity during sleep and its relationships with sleep architecture, depression severity, and responsivity to antidepressant treatment. MethodsPolysomnography was recorded in 38 patients with MDD (in unmedicated and 7-day-medicated states) and 38 age-matched healthy control subjects (N= 76). The aperiodic power component was calculated using irregularly resampled auto-spectral analysis. Depression severity was assessed with the Hamilton Depression Rating Scale. We replicated the analysis using 2 independently collected datasets of medicated patients and control subjects (N = 60 and N = 80, respectively). ResultsUnmedicated patients showed flatter aperiodic slopes compared with control subjects during non–rapid eye movement (non-REM) stage 2 sleep (p = .009). Medicated patients showed flatter aperiodic slopes compared with their earlier unmedicated state (p values < .001) and control subjects during all sleep stages (p values < .03). In medicated patients, flatter aperiodic slopes during non-REM sleep were linked to the higher proportion of N1, lower proportion of REM, delayed onset of N3 and REM, and shorter total sleep time. ConclusionsFlatter slopes of aperiodic electroencephalographic power may reflect noisier neural activity due to increased excitation-to-inhibition balance, representing a new disease-relevant feature of sleep in MDD.

Functional brain abnormalities in major depressive disorder using a multiscale community detection approach

Major depressive disorder (MDD) is a serious disease associated with abnormal brain regions, however, the interconnection between specific brain regions related to depression has not been fully explored. To solve this problem, the paper proposes a novel multiscale community detection method to compare the differences in brain regions between normal controls (NC) and MDD patients. This study adopted the Brainnetome Atlas to divide the brain into 246 regions and extract the time series of each region. The Pearson correlation was used to measure the similarity among different brain regions to conduct the brain functional network and to perform multiscale community detection. The optimal brain community structure of each group was further explored based on the modularized Qcut algorithm, normalized mutual information (NMI), and variation of information (VI). The Jaccard index was then applied to compare the abnormalities of each brain region from different community environments between the brain function networks of NC and MDD patients. The experiments revealed several abnormal brain regions between NC and MDD, including the superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, orbital gyrus, superior temporal gyrus, middle temporal gyrus, inferior temporal gyrus, posterior superior temporal sulcus, inferior parietal gyrus, precuneus, postcentral gyrus, insular gyrus, cingulate gyrus, hippocampus and basal ganglia. Finally, a new subnetwork related to cognitive function was discovered, which was composed of the island gyrus and inferior frontal gyrus. All experiments indicated that the proposed method is useful in detecting functional brain abnormalities in MDD, and it can provide valuable insights into the diagnosis and treatment of MDD.

Insular-associated causal network of structural covariance evaluating progressive gray matter changes in major depressive disorder.

Morphometric studies demonstrated wide-ranging distribution of brain structural abnormalities in major depressive disorder (MDD). This study explored the progressive gray matter volume (GMV) changes pattern of structural network in 108 MDD patients throughout the illness duration by using voxel-based morphometric analysis. The causal structural covariance network method was applied to map the causal effects of GMV alterations between the original source of structural changes and other brain regions as the illness duration prolonged in MDD. This was carried out by utilizing the Granger causality analysis to T1-weighted data ranked based on the disease progression information. With greater illness duration, the GMV reduction was originated from the right insula and progressed to the frontal lobe, and then expanded to the occipital lobe, temporal lobe, dorsal striatum (putamen and caudate) and the cerebellum. Importantly, results revealed that the right insula was the prominent node projecting positive causal influences (i.e., GMV decrease) to frontal lobe, temporal lobe, postcentral gyrus, putamen, and precuneus. While opposite causal effects were detected from the right insula to the angular, parahippocampus, supramarginal gyrus and cerebellum. This work may provide further information and vital evidence showing that MDD is associated with progressive brain structural alterations.

Distinct stress-related medial prefrontal cortex activation in women with depression with and without childhood maltreatment.

Emerging evidence has highlighted the moderating effect of childhood maltreatment (CM) in shaping neurobiological abnormalities in major depressive disorder (MDD). However, whether neural mechanisms underlying stress sensitivity in MDD are affected by the history of CM is unclear. Two hundred and thirteen medication-free female participants were recruited for a functional magnetic resonance imaging study assessing the effects of psychosocial stress on neural responses. The Montreal Imaging Stress Task was administrated to 44 female MDD patients with CM (MDD/CM), 32 female MDD patients without CM (MDD/noCM), 43 female healthy controls (HCs) with CM (HC/CM), and 94 female HCs without CM (HC/noCM). A CM (CM, noCM) × diagnosis (MDD, HC) whole-brain voxel-wise analysis was run to assess putative group differences in neural stress responses. A significant CM × Diagnosis interaction emerged in the medial prefrontal cortex (mPFC). Bonferroni-corrected simple effects analysis clarified that (1) the MDD/CM group had less mPFC deactivation than the HC/CM group, (2) the MDD/noCM group exhibited greater mPFC deactivation than the HC/noCM group, and (3) the MDD/CM group exhibited less mPFC deactivation relative to the MDD/noCM group. In addition, the mPFC-seed psychophysiological interaction analysis revealed that individuals in the CM groups had significantly greater stress-related mPFC-left superior frontal gyrus and mPFC-right posterior cerebellum connectivity relative to the noCM groups. Findings highlight distinct neural abnormalities in MDD depending on prior CM history, particularly potentiated stress-related mPFC recruitment among MDD individuals reporting CM. Moreover, CM history was generally associated with the disruption in functional connectivity centered on the mPFC.

An aberrant hippocampal subregional network, rather than structure, characterizes major depressive disorder

BackgroundBehavioral and neuroimaging studies have implicated the hippocampus as a cardinal neural structure in major depressive disorder (MDD) pathogenesis. The hippocampal subregion-specific structural and functional abnormalities in MDD remain unknown. MethodsMultimodal magnetic resonance imaging (MRI) was acquired in 140 patients with MDD and 44 age- and sex-matched healthy controls (HCs). We quantified hippocampal subregional volumes and fractional anisotropy (FA) following a structural and diffusion MRI data analysis processing stream. Hippocampal subregional networks were established using seed-based functional connectivity (FC) analysis. Univariate analysis was used to investigate the differences between the two groups. Significant subfield metrics were correlated with depression severity. ResultsCompared with HCs, we did not find significant differences in subregional volumes or FA metrics in the MDD group. The MDD group exhibited a significantly weaker connectivity of the right hippocampal subregional networks with the temporal cortex (extending to the insula) and basal ganglia but showed increased connectivity of the right subiculum to the bilateral lingual gyrus. The FC between the right cornu ammonis 1 and right fusiform, between the right hippocampal amygdala transition area and the bilateral basal ganglia, were negatively correlated with depression severity (r = −0.224, p = 0.010; r = −0.196, p = 0.025, respectively) in the MDD group. LimitationsThis study did not consider the longitudinal changes in the structure and functional connectivity of the hippocampal subregion. ConclusionThese findings advance our understanding of the neurobiological basis of depression by identifying the hippocampal subregional structural and functional abnormalities.

Sex-specific neural responses to acute psychosocial stress in depression

Major Depressive Disorder (MDD) is characterized by increased stress sensitivity. Emerging findings in healthy adults suggest that stress responses within limbic/striatal-prefrontal regions are moderated by sex and unfold over time. Thus, we hypothesized that stress response abnormalities in MDD might be affected by sex and stress exposure time. The Montreal Imaging Stress Task was administered to 124 unmedicated patients with first-episode MDD (76 females) and 243 healthy controls (HC; 137 females) during functional magnetic resonance imaging (fMRI). Based on prior studies, amygdala, hippocampus, medial orbitofrontal cortex (mOFC), nucleus accumbens (NAc) and dorsolateral prefrontal cortex (dlPFC) were selected as a priori regions of interest. In a complementary approach, we probed the effects of stress on the frontoparietal network (FPN) and a network including the amygdala, NAc and anterior cingulate cortex (ACC). Across groups, males exhibited higher dlPFC activity and right FPN amplitude than females. Relative to female HCs, the female MDD group had less deactivation in limbic/striatal regions (amygdala, NAc, hippocampus, Amygdala-NAc-ACC network). Furthermore, unlike female HCs, the female MDD group failed to show a significant increase of deactivation over stress exposure time in the amygdala, mOFC and NAc. Our findings confirm the importance of considering sex differences when investigating neural stress responses. Case-control differences in neural stress responses observed in females (but not males) provide insights into sex differences in the etiology and pathophysiology of depression. The failure to deactivate limbic/NAc regions in depressed females point to dysfunction of adaptive stress responses over stress exposure time.

Differential reinforcement learning responses to positive and negative information in unmedicated individuals with depression

Major depressive disorder (MDD) is characterized by behavioral and neural abnormalities in processing both rewarding and aversive stimuli, which may impact motivational and affective symptoms. Learning paradigms have been used to assess reinforcement encoding abnormalities in MDD and their association with dysfunctional incentive-based behavior, but how the valence and context of information modulate this learning is not well understood. To address these gaps, we examined responses to positive and negative reinforcement across multiple temporal phases of information processing. While undergoing functional magnetic resonance imaging (fMRI), 47 participants (23 unmedicated, predominantly medication-naïve participants with MDD and 24 demographically-matched HC participants) completed a probabilistic, feedback-based reinforcement learning task that allowed us to separate neural activation during motor response (choice) from reinforcement feedback and monetary outcome across two independent conditions: pursuing gains and avoiding losses. In the gain condition, MDD participants showed overall blunted learning responses (prediction error) in the dorsal striatum when receiving monetary outcome, and reduced responses in ventral striatum for positive, but not negative, prediction error. The MDD group showed enhanced sensitivity to negative information, and symptom severity was associated with better behavioral performance in the loss condition. These findings suggest that striatal responses during learning are abnormal in individuals with MDD but vary with the valence of information.