Multimodal Abnormalities of Brain Structure and Function in Major Depressive Disorder: A Meta-Analysis of Neuroimaging Studies

Disrupted functional connectivity of bilateral nucleus accumbens in major depressive disorder with and without melancholic features

Our study aims to explore the differences in functional connectivity in the nucleus accumbens (NAc) between patients with melancholic depression and non-melancholic depression (NMD) and their relation to melancholic depression's pathogenesis. We recruited 60 melancholic depression, 58 NMD, and 80 healthy controls, all matched for gender, age, and education. Functional connectivity analysis focused on bilateral NAc as the region of interest, comparing it with the whole brain and correlating significant differences with clinical scores. Melancholic depression patients showed reduced functional connectivity between the left NAc and anterior brain regions, and between the right NAc and temporal and frontal areas, compared to healthy controls. In contrast, NMD patients displayed reduced functional connectivity only between the left NAc and the posterior cingulate cortex. Melancholic depression patients also exhibited increased functional connectivity between the right NAc and the middle frontal gyrus, unlike NMD patients. The findings suggest that melancholic depression patients exhibit unique NAc functional connectivity patterns, particularly with the default mode network and prefrontal areas, suggesting atypical reward-circuitry interactions. The right NAc's connection to the prefrontal gyrus may distinguish melancholic depression from NMD.

Mesenchymal stem cells improve depressive disorder via inhibiting the inflammatory polarization of microglia

Depressive disorder (DD) ranks among the most prevalent, burdensome, and costly psychiatric conditions globally. It manifests through a range of emotional, cognitive, somatic, and behavioral symptoms. Mesenchymal Stem Cells (MSCs) have garnered significant attention due to their therapeutic potential via immunomodulation in neurological disorders. Our research indicates that MSCs treatment demonstrates a notable effect on a Chronic Unpredictable Mild Stress (CUMS)-induced DD model in mice, surpassing even Fluoxetine in its antidepressant efficacy. MSCs mitigate DD by inhibiting central nervous system inflammation and facilitating the conversion of microglial cells into an Arg1high anti-inflammatory state. The MSCs-derived TGF-β1 is crucial for this Arg1high microglial cell transformation in DD treatment.

Transdiagnostic depression severity and its relationship to global and prefrontal-amygdala structural properties in people with major depression and post-traumatic stress disorder

While some studies have used a transdiagnostic approach to relate depression to metabolic or functional brain alterations, the structural substrate of depression across clinical diagnostic categories is underexplored. In a cross-sectional study of 52 patients with major depressive disorder and 51 with post-traumatic stress disorder, drug-naïve, and spanning mild to severe depression severity, we examined transdiagnostic depressive correlates with regional gray matter volume and the topological properties of gray matter-based networks. Locally, transdiagnostic depression severity correlated positively with gray matter volume in the right middle frontal gyrus and negatively with nodal topological properties of gray matter-based networks in the right amygdala. Globally, transdiagnostic depression severity correlated positively with normalized characteristic path length, a measure implying brain integration ability. Compared with 62 healthy control participants, both major depressive disorder and post-traumatic stress disorder patients showed altered nodal properties in regions of the fronto-limbic-striatal circuit, and global topological organization in major depressive disorder in particular was characterized by decreased integration and segregation. These findings provide evidence for a gray matter-based structural substrate underpinning depression, with the prefrontal-amygdala circuit a potential predictive marker for depressive symptoms across clinical diagnostic categories.

COVID-19 is associated with changes in brain function and structure: A multimodal meta-analysis of neuroimaging studies

The actual role of coronavirus disease 2019 (COVID-19) in brain damage has been increasingly reported, necessitating a meta-analysis to collate and summarize the inconsistent findings from functional imaging and voxel-based morphometry (VBM) studies. A comprehensive voxel-wise meta-analysis of the whole brain was conducted to identify alterations in functional activity and gray matter volume (GMV) between COVID-19 patients and healthy controls (HCs) by using Seed-based d Mapping software. We included 15 functional imaging studies (484 patients with COVID-19, 534 HCs) and 9 VBM studies (449 patients with COVID-19, 388 HCs) in the analysis. Overall, patients with COVID-19 exhibited decreased functional activity in the right superior temporal gyrus (STG) (extending to the right middle and inferior temporal gyrus, insula, and temporal pole [TP]), left insula, right orbitofrontal cortex (OFC) (extending to the right olfactory cortex), and left cerebellum compared to HCs. For VBM, patients with COVID-19, relative to HCs, showed decreased GMV in the bilateral anterior cingulate cortex/medial prefrontal cortex (extending to the bilateral OFC), and left cerebellum, and increased GMV in the bilateral amygdala (extending to the bilateral hippocampus, STG, TP, MTG, and right striatum). Moreover, overlapping analysis revealed that patients with COVID-19 exhibited both decreased functional activity and increased GMV in the right TP (extending to the right STG). The multimodal meta-analysis suggests that brain changes of function and structure in the temporal lobe, OFC and cerebellum, and functional or structural alterations in the insula and the limbic system in COVID-19. These findings contribute to a better understanding of the pathophysiology of brain alterations in COVID-19. SIGNIFICANCE STATEMENT: This first large-scale multimodal meta-analysis collates existing neuroimaging studies and provides voxel-wise functional and structural whole-brain abnormalities in COVID-19. Findings of this meta-analysis provide valuable insights into the dynamic brain changes (from infection to recovery) and offer further explanations for the pathophysiological basis of brain alterations in COVID-19.

Potential correlations between asymmetric disruption of functional connectivity and metabolism in major depressive disorder

OBJECTIVE

Previous research has suggested a connection between major depressive disorder (MDD) and certain comorbidities, including gastrointestinal issues, thyroid dysfunctions, and glycolipid metabolism abnormalities. However, the relationships between these factors and asymmetrical alterations in functional connectivity (FC) in adults with MDD remain unclear.

METHOD

We conducted a study on a cohort of 42 MDD patients and 42 healthy controls (HCs). Participants underwent comprehensive clinical assessments, including evaluations of blood lipids and thyroid hormone levels, as well as resting-state functional magnetic resonance imaging (Rs-fMRI) scans. Data analysis involved correlation analysis to compute the parameter of asymmetry (PAS) for the entire brain's functional connectome. We then examined the interrelationships between abnormal PAS regions in the brain, thyroid hormone levels, and blood lipid levels.

RESULTS

The third-generation ultra-sensitive thyroid stimulating hormone (TSH3UL) level was found to be significantly lower in MDD patients compared to HCs. The PAS score of the left inferior frontal gyrus (IFG) decreased, while the bilateral posterior cingulate cortex (Bi-PCC) PAS increased in MDD patients relative to HCs. Notably, the PAS score of the left IFG negatively correlated with both TSH and total cholesterol (CHOL) levels. However, these correlations lose significance after the Bonferroni correction.

CONCLUSION

MDD patients demonstrated abnormal asymmetry in resting-state FC (Rs-FC) within the fronto-limbic system, which may be associated with CHOL and thyroid hormone levels.

Integrative molecular and structural neuroimaging analyses of the interaction between depression and age of onset: A multimodal magnetic resonance imaging study

Depression is a neurodevelopmental disorder that exhibits progressive gray matter volume (GMV) atrophy. Research indicates that brain development is influential in depression-induced GMV alterations. However, the interaction between depression and age of onset is not well understood by the underlying molecular and neuropathological mechanisms. Thus, 152 first-episode depression individuals and matched 130 healthy controls (HCs) were recruited to undergo T1-weighted high-resolution magnetic resonance imaging for this study. By two-way ANOVA, age and diagnosis were used as factors when analyzing the interaction of GMV in the participants. Then, spatial correlations between neurotransmitter maps and factor-related volume maps are established. Results illustrate a pronounced antagonistic interaction between depression and age of onset in the right insula, superior temporal gyrus, anterior cingulate gyrus, and orbitofrontal gyrus. Depression-caused reductions in GMV are mainly distributed in thalamic-limbic-cortical regions, regardless of age. For the main effect of age, adults exhibit brain atrophy in frontal, cerebellum, parietal, and temporal lobe structures. Cross-modal correlations showed that GMV changes in the interactive regions were linked with the serotonergic system and dopaminergic systems. Summarily, our results reveal the interaction between depression and age of onset in neurobiological mechanisms, which provide hints for future treatment of different ages of depression.

Convergent functional effects of antidepressants in major depressive disorder: a neuroimaging meta-analysis

Background

Neuroimaging studies have provided valuable insights into the macroscale impacts of antidepressants on brain functions in patients with major depressive disorder. However, the findings of individual studies are inconsistent. Here, we aimed to provide a quantitative synthesis of the literature to identify convergence of the reported findings at both regional and network levels and to examine their associations with neurotransmitter systems.

Methods

Through a comprehensive search in PubMed and Scopus databases, we reviewed 5,258 abstracts and identified 36 eligible functional neuroimaging studies on antidepressant effects in major depressive disorder. Activation likelihood estimation was used to investigate regional convergence of the reported foci of consistent antidepressant effects, followed by functional decoding and connectivity mapping of the convergent clusters. Additionally, utilizing group-averaged data from the Human Connectome Project, we assessed convergent resting-state functional connectivity patterns of the reported foci. Next, we compared the convergent circuit with the circuits targeted by transcranial magnetic stimulation (TMS) therapy. Last, we studied the association of regional and network-level convergence maps with selected neurotransmitter receptors/transporters maps.

Results

No regional convergence was found across foci of treatment-associated alterations in functional imaging. Subgroup analysis across the Treated > Untreated contrast revealed a convergent cluster in the left dorsolateral prefrontal cortex, which was associated with working memory and attention behavioral domains. Moreover, we found network-level convergence of the treatment-associated alterations in a circuit more prominent in the frontoparietal areas. This circuit was co-aligned with circuits targeted by "anti-subgenual" and "Beam F3" TMS therapy. We observed no significant correlations between our meta-analytic findings with the maps of neurotransmitter receptors/transporters.

Conclusion

Our findings highlight the importance of the frontoparietal network and the left dorsolateral prefrontal cortex in the therapeutic effects of antidepressants, which may relate to their role in improving executive functions and emotional processing.

Insomnia-related brain functional correlates in first-episode drug-naïve major depressive disorder revealed by resting-state fMRI

Introduction

Insomnia is a common comorbidity symptom in major depressive disorder (MDD) patients. Abnormal brain activities have been observed in both MDD and insomnia patients, however, the central pathological mechanisms underlying the co-occurrence of insomnia in MDD patients are still unclear. This study aimed to explore the differences of spontaneous brain activity between MDD patients with and without insomnia, as well as patients with different level of insomnia.

Methods

A total of 88 first-episode drug-naïve MDD patients including 44 with insomnia (22 with high insomnia and 22 with low insomnia) and 44 without insomnia, as well as 44 healthy controls (HC), were enrolled in this study. The level of depression and insomnia were evaluated by HAMD-17, adjusted HAMD-17 and its sleep disturbance subscale in all subjects. Resting-state functional and structural magnetic resonance imaging data were acquired from all participants and then were preprocessed by the software of DPASF. Regional homogeneity (ReHo) values of brain regions were calculated by the software of REST and were compared. Finally, receiver operating characteristic (ROC) curves were conducted to determine the values of abnormal brain regions for identifying MDD patients with insomnia and evaluating the severity of insomnia.

Results

Analysis of variance showed that there were significant differences in ReHo values in the left middle frontal gyrus, left pallidum, right superior frontal gyrus, right medial superior frontal gyrus and right rectus gyrus among three groups. Compared with HC, MDD patients with insomnia showed increased ReHo values in the medial superior frontal gyrus, middle frontal gyrus, triangular inferior frontal gyrus, calcarine fissure and right medial superior frontal gyrus, medial orbital superior frontal gyrus, as well as decreased ReHo values in the left middle occipital gyrus, pallidum and right superior temporal gyrus, inferior temporal gyrus, middle cingulate gyrus, hippocampus, putamen. MDD patients without insomnia demonstrated increased ReHo values in the left middle frontal gyrus, orbital middle frontal gyrus, anterior cingulate gyrus and right triangular inferior frontal gyrus, as well as decreased ReHo values in the left rectus gyrus, postcentral gyrus and right rectus gyrus, fusiform gyrus, pallidum. In addition, MDD patients with insomnia had decreased ReHo values in the left insula when compared to those without insomnia. Moreover, MDD patients with high insomnia exhibited increased ReHo values in the right middle temporal gyrus, and decreased ReHo values in the left orbital superior frontal gyrus, lingual gyrus, right inferior parietal gyrus and postcentral gyrus compared to those with low insomnia. ROC analysis demonstrated that impaired brain region might be helpful for identifying MDD patients with insomnia and evaluating the severity of insomnia.

Conclusion

These findings suggested that MDD patients with insomnia had wider abnormalities of brain activities in the prefrontal-limbic circuits including increased activities in the prefrontal cortex, which might be the compensatory mechanism underlying insomnia in MDD. In addition, decreased activity of left insula might be associated with the occurrence of insomnia in MDD patients and decreased activities of the frontal-parietal network might cause more serious insomnia related to MDD.

Nutritional Strategies in Major Depression Disorder: From Ketogenic Diet to Modulation of the Microbiota-Gut-Brain Axis

Major depressive disorder (MDD) is a leading cause of disability worldwide. While traditional pharmacological treatments are effective for many cases, a significant proportion of patients do not achieve full remission or experience side effects. Nutritional interventions hold promise as an alternative or adjunctive approach, especially for treatment-resistant depression. This review examines the potential role of nutrition in managing MDD through addressing biological deficits and modulating pathways relevant to its pathophysiology. Specifically, it explores the ketogenic diet and gut microbiome modulation through various methods, including probiotics, prebiotics, synbiotics, postbiotics, and fecal microbiota transplantation. Numerous studies link dietary inadequacies to increased MDD risk and deficiencies in nutrients like omega-3 s, vitamins D and B, magnesium, and zinc. These deficiencies impact neurotransmitters, inflammation, and other biological factors in MDD. The gut-brain axis also regulates mood, stress response, and immunity, and disruptions are implicated in MDD. While medications aid acute symptoms, nutritional strategies may improve long-term outcomes by preventing relapse and promoting sustained remission. This comprehensive review aims to provide insights into nutrition's multifaceted relationship with MDD and its potential for developing more effective integrated treatment approaches.

Meta-analysis of variance in tDCS effects on response inhibition

Deficiencies in response inhibition are associated with numerous mental health conditions, warranting innovative treatments. Transcranial direct current stimulation (tDCS), a non-invasive brain stimulation technique, modulates cortical excitability and has shown promise in improving response inhibition. However, tDCS effects on response inhibition often yield contradictory findings. Previous research emphasized the importance of inter-individual factors that are mostly ignored in conventional meta-analyses of mean effects. We aimed to fill this gap and promote the complementary use of the coefficient of variation ratio and standardized mean effects. The systematic literature search included single-session and sham-controlled tDCS studies utilizing stop-signal task or Go-NoGo tasks, analyzing 88 effect sizes from 53 studies. Considering the impact of inter-individual factors, we hypothesized that variances increase in the active versus sham tDCS. However, the results showed that variances between both groups did not differ. Additionally, analyzing standardized mean effects supported previous research showing an improvement in the stop-signal task but not in the Go-NoGo task following active tDCS. These findings suggest that inter-individual differences do not increase variances in response inhibition, implying that the heterogeneity cannot be attributed to higher variance in response inhibition during and after active tDCS. Furthermore, methodological considerations are crucial for tDCS efficacy.

Unraveling robust brain-behavior links of depressive complaints through granular network models for understanding heterogeneity

BACKGROUND

Depressive symptoms are highly prevalent, present in heterogeneous symptom patterns, and share diverse neurobiological underpinnings. Understanding the links between psychopathological symptoms and biological factors is critical in elucidating its etiology and persistence. We aimed to evaluate the utility of using symptom-brain network models to parse the heterogeneity of depressive complaints in a large adolescent sample.

METHODS

We used data from the third wave of the IMAGEN study, a multi-center panel cohort study involving 1317 adolescents (52.49 % female, mean ± SD age = 18.5 ± 0.7). Two network models were estimated: one including an overall depressive symptom severity sum score based on the Adolescent Depression Rating Scale (ADRS), and one incorporating individual ADRS item scores. Both networks included measures of cortical thickness in several regions (insula, cingulate, mOFC, fusiform gyrus) and hippocampal volume derived from neuroimaging.

RESULTS

The network based on individual item scores revealed associations between cortical thickness measures and specific depressive complaints, obscured when using an aggregate depression severity score. Notably, the insula's cortical thickness showed negative associations with cognitive dysfunction (partial cor. = -0.15); the cingulate's cortical thickness showed negative associations with feelings of worthlessness (partial cor. = -0.10), and mOFC was negatively associated with anhedonia (partial cor. = -0.05).

LIMITATIONS

This cross-sectional study relied on the self-reported assessment of depression complaints and used a non-clinical sample with predominantly healthy participants (19 % with depression or sub-threshold depression).

CONCLUSIONS

This study showcases the utility of network models in parsing heterogeneity in depressive complaints, linking individual complaints to specific neural substrates. We outline the next steps to integrate neurobiological and cognitive markers to unravel MDD's phenotypic heterogeneity.

Transcriptomic decoding of regional cortical vulnerability to major depressive disorder

Previous studies in small samples have identified inconsistent cortical abnormalities in major depressive disorder (MDD). Despite genetic influences on MDD and the brain, it is unclear how genetic risk for MDD is translated into spatially patterned cortical vulnerability. Here, we initially examined voxel-wise differences in cortical function and structure using the largest multi-modal MRI data from 1660 MDD patients and 1341 controls. Combined with the Allen Human Brain Atlas, we then adopted transcription-neuroimaging spatial correlation and the newly developed ensemble-based gene category enrichment analysis to identify gene categories with expression related to cortical changes in MDD. Results showed that patients had relatively circumscribed impairments in local functional properties and broadly distributed disruptions in global functional connectivity, consistently characterized by hyper-function in associative areas and hypo-function in primary regions. Moreover, the local functional alterations were correlated with genes enriched for biological functions related to MDD in general (e.g., endoplasmic reticulum stress, mitogen-activated protein kinase, histone acetylation, and DNA methylation); and the global functional connectivity changes were associated with not only MDD-general, but also brain-relevant genes (e.g., neuron, synapse, axon, glial cell, and neurotransmitters). Our findings may provide important insights into the transcriptomic signatures of regional cortical vulnerability to MDD.

Status and trends of TMS research in depressive disorder: a bibliometric and visual analysis

Background

Depression is a chronic psychiatric condition that places significant burdens on individuals, families, and societies. The rapid evolution of non-invasive brain stimulation techniques has facilitated the extensive clinical use of Transcranial Magnetic Stimulation (TMS) for depression treatment. In light of the substantial recent increase in related research, this study aims to employ bibliometric methods to systematically review the global research status and trends of TMS in depression, providing a reference and guiding future studies in this field.

Methods

We retrieved literature on TMS and depression published between 1999 and 2023 from the Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) databases within the Web of Science Core Collection (WoSCC). Bibliometric analysis was performed using VOSviewer and CiteSpace software to analyze data on countries, institutions, authors, journals, keywords, citations, and to generate visual maps.

Results

A total of 5,046 publications were extracted covering the period from 1999 to 2023 in the field of TMS and depression. The publication output exhibited an overall exponential growth trend. These articles were published across 804 different journals, BRAIN STIMULATION is the platform that receives the most articles in this area. The literature involved contributions from over 16,000 authors affiliated with 4,573 institutions across 77 countries. The United States contributed the largest number of publications, with the University of Toronto and Daskalakis ZJ leading as the most prolific institution and author, respectively. Keywords such as "Default Mode Network," "Functional Connectivity," and "Theta Burst" have recently garnered significant attention. Research in this field primarily focuses on TMS stimulation patterns, their therapeutic efficacy and safety, brain region and network mechanisms under combined brain imaging technologies, and the modulation effects of TMS on brain-derived neurotrophic factor (BDNF) and neurotransmitter levels.

Conclusion

In recent years, TMS therapy has demonstrated extensive potential applications and significant implications for the treatment of depression. Research in the field of TMS for depression has achieved notable progress. Particularly, the development of novel TMS stimulation patterns and the integration of TMS therapy with multimodal techniques and machine learning algorithms for precision treatment and investigation of brain network mechanisms have emerged as current research hotspots.

Brain Network Localization of Gray Matter Atrophy and Neurocognitive and Social Cognitive Dysfunction in Schizophrenia

BACKGROUND

Numerous studies have established the presence of gray matter atrophy and brain activation abnormalities during neurocognitive and social cognitive tasks in schizophrenia. Despite a growing consensus that diseases localize better to distributed brain networks than individual anatomical regions, relatively few studies have examined brain network localization of gray matter atrophy and neurocognitive and social cognitive dysfunction in schizophrenia.

METHODS

To address this gap, we initially identified brain locations of structural and functional abnormalities in schizophrenia from 301 published neuroimaging studies with 8712 individuals with schizophrenia and 9275 healthy control participants. By applying novel functional connectivity network mapping to large-scale resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 brain abnormality networks of schizophrenia.

RESULTS

The gray matter atrophy network of schizophrenia comprised a broadly distributed set of brain areas predominantly implicating the ventral attention, somatomotor, and default networks. The neurocognitive dysfunction network was also composed of widespread brain areas primarily involving the frontoparietal and default networks. By contrast, the social cognitive dysfunction network consisted of circumscribed brain regions mainly implicating the default, subcortical, and visual networks.

CONCLUSIONS

Our findings suggest shared and unique brain network substrates of gray matter atrophy and neurocognitive and social cognitive dysfunction in schizophrenia, which may not only refine the understanding of disease neuropathology from a network perspective but may also contribute to more targeted and effective treatments for impairments in different cognitive domains in schizophrenia.

The neurostructural consequences of glaucoma and their overlap with disorders exhibiting emotional dysregulations: A voxel-based meta-analysis and tripartite system model

BACKGROUND

Glaucoma, a progressive neurodegenerative disorder leading to irreversible blindness, is associated with heightened rates of generalized anxiety and depression. This study aims to comprehensively investigate brain morphological changes in glaucoma patients, extending beyond visual processing areas, and explores overlaps with morphological alterations observed in anxiety and depression.

METHODS

A comparative meta-analysis was conducted, using case-control studies of brain structural integrity in glaucoma patients. We aimed to identify regions with gray matter volume (GMV) changes, examine their role within distinct large-scale networks, and assess overlap with alterations in generalized anxiety disorder (GAD) and major depressive disorder (MDD).

RESULTS

Glaucoma patients exhibited significant GMV reductions in visual processing regions (lingual gyrus, thalamus). Notably, volumetric reductions extended beyond visual systems, encompassing the left putamen and insula. Behavioral and functional network decoding revealed distinct large-scale networks, implicating visual, motivational, and affective domains. The insular region, linked to pain and affective processes, displayed reductions overlapping with alterations observed in GAD.

LIMITATIONS

While the study identified significant morphological alterations, the number of studies from both the glaucoma and GAD cohorts remains limited due to the lack of independent studies meeting our inclusion criteria.

CONCLUSION

The study proposes a tripartite brain model for glaucoma, with visual processing changes related to the lingual gyrus and additional alterations in the putamen and insular regions tied to emotional or motivational functions. These neuroanatomical changes extend beyond the visual system, implying broader implications for brain structure and potential pathological developments, providing insights into the overall neurological consequences of glaucoma.

From Perspective of Hippocampal Plasticity: Function of Antidepressant Chinese Medicine Xiaoyaosan

The hippocampus is one of the most commonly studied brain regions in the context of depression. The volume of the hippocampus is significantly reduced in patients with depression, which severely disrupts hippocampal neuroplasticity. However, antidepressant therapies that target hippocampal neuroplasticity have not been identified as yet. Chinese medicine (CM) can slow the progression of depression, potentially by modulating hippocampal neuroplasticity. Xiaoyaosan (XYS) is a CM formula that has been clinically used for the treatment of depression. It is known to protect Gan (Liver) and Pi (Spleen) function, and may exert its antidepressant effects by regulating hippocampal neuroplasticity. In this review, we have summarized the association between depression and aberrant hippocampal neuroplasticity. Furthermore, we have discussed the researches published in the last 30 years on the effects of XYS on hippocampal neuroplasticity in order to elucidate the possible mechanisms underlying its therapeutic action against depression. The results of this review can aid future research on XYS for the treatment of depression.

Gut proinflammatory bacteria is associated with abnormal functional connectivity of hippocampus in unmedicated patients with major depressive disorder

Accumulating evidence has revealed the gut bacteria dysbiosis and brain hippocampal functional and structural alterations in major depressive disorder (MDD). However, the potential relationship between the gut microbiota and hippocampal function alterations in patients with MDD is still very limited. Data of resting-state functional magnetic resonance imaging were acquired from 44 unmedicated MDD patients and 42 demographically matched healthy controls (HCs). Severn pairs of hippocampus subregions (the bilateral cornu ammonis [CA1-CA3], dentate gyrus (DG), entorhinal cortex, hippocampal-amygdaloid transition area, and subiculum) were selected as the seeds in the functional connectivity (FC) analysis. Additionally, fecal samples of participants were collected and 16S rDNA amplicon sequencing was used to identify the altered relative abundance of gut microbiota. Then, association analysis was conducted to investigate the potential relationships between the abnormal hippocampal subregions FC and microbiome features. Also, the altered hippocampal subregion FC values and gut microbiota levels were used as features separately or together in the support vector machine models distinguishing the MDD patients and HCs. Compared with HCs, patients with MDD exhibited increased FC between the left hippocampus (CA2, CA3 and DG) and right hippocampus (CA2 and CA3), and decreased FC between the right hippocampal CA3 and bilateral posterior cingulate cortex. In addition, we found that the level of proinflammatory bacteria (i.e., Enterobacteriaceae) was significantly increased, whereas the level of short-chain fatty acids producing-bacteria (i.e., Prevotellaceae, Agathobacter and Clostridium) were significantly decreased in MDD patients. Furthermore, FC values of the left hippocampal CA3- right hippocampus (CA2 and CA3) was positively correlated with the relative abundance of Enterobacteriaceae in patients with MDD. Moreover, altered hippocampal FC patterns and gut microbiota level were considered in combination, the best discrimination was obtained (AUC = 0.92). These findings may provide insights into the potential role of gut microbiota in the underlying neuropathology of MDD patients.

Altered activation of the dorsal anterior cingulate cortex during oddball performance in individuals at risk for Alzheimer's disease

INTRODUCTION

The neural mechanisms underlying neurodegenerative disorders in the elderly remain elusive, despite extensive neuroimaging research in recent decades. Amnestic type mild cognitive impairment (aMCI) and late-life major depressive disorder (MDD) are two such conditions characterized by intersecting cognitive and affective symptomatology, and they are at a higher risk for Alzheimer's disease.

MATERIALS AND METHODS

This study analyzed the neural underpinnings of cognitive and depressive symptoms in a cohort comprising 12 aMCI subjects, 24 late-life MDD patients, and 26 healthy controls (HCs). Participants underwent a detailed neuropsychological assessment and completed a visual attentional oddball task during functional magnetic resonance imaging (fMRI), with evaluations at baseline and at 2-year follow-up.

RESULTS

Initial findings showed that aMCI subjects had reduced dACC activation during oddball (target) stimulus detection, a pattern that persisted in longitudinal analyses and correlated with cognitive functioning measures. For HCs, subsequent dACC activation was linked to depression scores. Furthermore, in the affective-cognitive altered groups, later dACC activation correlated with oddball and memory performance.

CONCLUSIONS

These findings enhance our comprehension of the neurobiological basis of cognitive and depressive disturbances in aging, indicating that dACC activation in response to a visual attentional oddball task could serve as a neural marker for assessing cognitive impairment and depression in conditions predisposing to Alzheimer's disease.

Convergent functional change of frontoparietal network in obsessive-compulsive disorder: a voxel-based meta-analysis

Background

Obsessive-compulsive disorder (OCD) is a chronic psychiatric illness with complex clinical manifestations. Cognitive dysfunction may underlie OC symptoms. The frontoparietal network (FPN) is a key region involved in cognitive control. However, the findings of impaired FPN regions have been inconsistent. We employed meta-analysis to identify the fMRI-specific abnormalities of the FPN in OCD.

Methods

PubMed, Web of Science, Scopus, and EBSCOhost were searched to screen resting-state functional magnetic resonance imaging (rs-fMRI) studies exploring dysfunction in the FPN of OCD patients using three indicators: the amplitude of low-frequency fluctuation/fractional amplitude of low-frequency fluctuation (ALFF/fALFF), regional homogeneity (ReHo) and functional connectivity (FC). We compared all patients with OCD and control group in a primary analysis, and divided the studies by medication in secondary meta-analyses with the activation likelihood estimation (ALE) algorithm.

Results

A total of 31 eligible studies with 1359 OCD patients (756 men) and 1360 healthy controls (733 men) were included in the primary meta-analysis. We concluded specific changes in brain regions of FPN, mainly in the left dorsolateral prefrontal cortex (DLPFC, BA9), left inferior frontal gyrus (IFG, BA47), left superior temporal gyrus (STG, BA38), right posterior cingulate cortex (PCC, BA29), right inferior parietal lobule (IPL, BA40) and bilateral caudate. Additionally, altered connectivity within- and between-FPN were observed in the bilateral DLPFC, right cingulate gyrus and right thalamus. The secondary analyses showed improved convergence relative to the primary analysis.

Conclusion

OCD patients showed dysfunction FPN, including impaired local important nodal brain regions and hypoconnectivity within the FPN (mainly in the bilateral DLPFC), during the resting state. Moreover, FPN appears to interact with the salience network (SN) and default mode network (DMN) through pivotal brain regions. Consistent with the hypothesis of fronto-striatal circuit dysfunction, especially in the dorsal cognitive circuit, these findings provide strong evidence for integrating two pathophysiological models of OCD.

Neural substrates of predicting anhedonia symptoms in major depressive disorder via connectome-based modeling

MAIN PROBLEM

Anhedonia is a critical diagnostic symptom of major depressive disorder (MDD), being associated with poor prognosis. Understanding the neural mechanisms underlying anhedonia is of great significance for individuals with MDD, and it encourages the search for objective indicators that can reliably identify anhedonia.

METHODS

A predictive model used connectome-based predictive modeling (CPM) for anhedonia symptoms was developed by utilizing pre-treatment functional connectivity (FC) data from 59 patients with MDD. Node-based FC analysis was employed to compare differences in FC patterns between melancholic and non-melancholic MDD patients. The support vector machines (SVM) method was then applied for classifying these two subtypes of MDD patients.

RESULTS

CPM could successfully predict anhedonia symptoms in MDD patients (positive network: r = 0.4719, p < 0.0020, mean squared error = 23.5125, 5000 iterations). Compared to non-melancholic MDD patients, melancholic MDD patients showed decreased FC between the left cingulate gyrus and the right parahippocampus gyrus (p_bonferroni = 0.0303). This distinct FC pattern effectively discriminated between melancholic and non-melancholic MDD patients, achieving a sensitivity of 93.54%, specificity of 67.86%, and an overall accuracy of 81.36% using the SVM method.

CONCLUSIONS

This study successfully established a network model for predicting anhedonia symptoms in MDD based on FC, as well as a classification model to differentiate between melancholic and non-melancholic MDD patients. These findings provide guidance for clinical treatment.

MDDOmics: multi-omics resource of major depressive disorder

Major depressive disorder (MDD) is a pressing global health issue. Its pathogenesis remains elusive, but numerous studies have revealed its intricate associations with various biological factors. Consequently, there is an urgent need for a comprehensive multi-omics resource to help researchers in conducting multi-omics data analysis for MDD. To address this issue, we constructed the MDDOmics database (Major Depressive Disorder Omics, (https://www.csuligroup.com/MDDOmics/), which integrates an extensive collection of published multi-omics data related to MDD. The database contains 41 222 entries of MDD research results and several original datasets, including Single Nucleotide Polymorphisms, genes, non-coding RNAs, DNA methylations, metabolites and proteins, and offers various interfaces for searching and visualization. We also provide extensive downstream analyses of the collected MDD data, including differential analysis, enrichment analysis and disease-gene prediction. Moreover, the database also incorporates multi-omics data for bipolar disorder, schizophrenia and anxiety disorder, due to the challenge in differentiating MDD from similar psychiatric disorders. In conclusion, by leveraging the rich content and online interfaces from MDDOmics, researchers can conduct more comprehensive analyses of MDD and its similar disorders from various perspectives, thereby gaining a deeper understanding of potential MDD biomarkers and intricate disease pathogenesis. Database URL: https://www.csuligroup.com/MDDOmics/.

Racial and ethnic socioenvironmental inequity and neuroimaging in psychiatry: a brief review of the past and recommendations for the future

Neuroimaging is a major tool that holds immense translational potential for understanding psychiatric disorder phenomenology and treatment. However, although epidemiological and social research highlights the many ways inequity and representativeness influences mental health, there is a lack of consideration of how such issues may impact neuroimaging features in psychiatric research. More specifically, the potential extent to which racialized inequities may affect underlying neurobiology and impact the generalizability of neural models of disorders is unclear. The present review synthesizes research focused on understanding the potential consequences of racial/ethnic inequities relevant to neuroimaging in psychiatry. We first discuss historical and contemporary drivers of inequities that persist today. We then discuss the neurobiological consequences of these inequities as revealed through current research, and note emergent research demonstrating the impact such inequities have on our ability to use neuroimaging to understand psychiatric disease. We end with a set of recommendations and practices to move the field towards more equitable approaches that will advance our abilities to develop truly generalizable neurobiological models of psychiatric disorders.

Population-level normative models reveal race- and socioeconomic-related variability in cortical thickness of threat neurocircuitry

The inequitable distribution of economic resources and exposure to adversity between racial groups contributes to mental health disparities within the United States. Consideration of the potential neurodevelopmental consequences, however, has been limited particularly for neurocircuitry known to regulate the emotional response to threat. Characterizing the consequences of inequity on threat neurocircuitry is critical for robust and generalizable neurobiological models of psychiatric illness. Here we use data from the Adolescent Brain and Cognitive Development Study 4.0 release to investigate the contributions of individual and neighborhood-level economic resources and exposure to discrimination. We investigate the potential appearance of race-related differences using both standard methods and through population-level normative modeling. We show that, in a sample of white and Black adolescents, racial inequities in socioeconomic factors largely contribute to the appearance of race-related differences in cortical thickness of threat neurocircuitry. The race-related differences are preserved through the use of population-level models and such models also preserve associations between cortical thickness and specific socioeconomic factors. The present findings highlight that such socioeconomic inequities largely underlie race-related differences in brain morphology. The present findings provide important new insight for the generation of generalizable neurobiological models of psychiatric illness.

Depressed patients with childhood maltreatment display altered intra- and inter-network resting state functional connectivity

BACKGROUND

Childhood maltreatment (CM) is a major risk factor for the development of major depressive disorder (MDD). To gain more knowledge on how adverse childhood experiences influence the development of brain architecture, we studied functional connectivity (FC) alterations of neural networks of depressed patients with, or without the history of CM.

METHODS

Depressed patients with severe childhood maltreatment (n = 18), MDD patients without maltreatment (n = 19), and matched healthy controls (n = 20) were examined with resting state functional MRI. History of maltreatment was assessed with the 28-item Childhood Trauma Questionnaire. Intra- and inter-network FC alterations were evaluated using FMRIB Software Library and CONN toolbox.

RESULTS

We found numerous intra- and inter-network FC alterations between the maltreated and the non-maltreated patients. Intra-network FC differences were found in the default mode, visual and auditory networks, and cerebellum. Network modelling revealed several inter-network FC alterations connecting the default mode network with the executive control, salience and cerebellar networks. Increased inter-network FC was found in maltreated patients between the sensory-motor and visual, cerebellar, default mode and salience networks.

LIMITATIONS

Relatively small sample size, cross-sectional design, and retrospective self-report questionnaire to assess adverse childhood experiences.

CONCLUSIONS

Our findings confirm that severely maltreated depressed patients display numerous alterations of intra- and inter-network FC strengths, not only in their fronto-limbic circuits, but also in sensory-motor, visual, auditory, and cerebellar networks. These functional alterations may explain that maltreated individuals typically display altered perception and are prone to develop functional neurological symptom disorder (conversion disorder) in adulthood.

Increased grey matter volumes in the temporal lobe and its relationship with cognitive functioning in euthymic patients with bipolar disorder

BACKGROUND

Bipolar disorder (BD) is characterized by episodic mood dysregulation, although a significant portion of patients suffer persistent cognitive impairment during euthymia. Previous magnetic resonance imaging (MRI) research suggests BD patients may have accelerated brain aging, observed as lower grey matter volumes. How these neurostructural alterations are related to the cognitive profile of BD is unclear.

METHODS

We aim to explore this relationship in euthymic BD patients with multimodal structural neuroimaging. A sample of 27 euthymic BD patients and 24 healthy controls (HC) underwent structural grey matter MRI and diffusion-weighted imaging (DWI). BD patient's cognition was also assessed. FreeSurfer algorithms were used to obtain estimations of regional grey matter volumes. White matter pathways were reconstructed using TRACULA, and four diffusion metrics were extracted. ANCOVA models were performed to compare BD patients and HC values of regional grey matter volume and diffusion metrics. Global brain measures were also compared. Bivariate Pearson correlations were explored between significant brain results and five cognitive domains.

RESULTS

Euthymic BD patients showed higher ventricular volume (F(1, 46) = 6.04; p = 0.018) and regional grey matter volumes in the left fusiform (F(1, 46) = 15.03; pFDR = 0.015) and bilateral parahippocampal gyri compared to HC (L: F(1, 46) = 12.79, pFDR = 0.025/ R: F(1, 46) = 15.25, pFDR = 0.015). Higher grey matter volumes were correlated with greater executive function (r = 0.53, p = 0.008).

LIMITATIONS

We evaluated a modest sample size with concurrent pharmacological treatment.

CONCLUSIONS

Higher medial temporal volumes in euthymic BD patients may be a potential signature of brain resilience and cognitive adaptation to a putative illness neuroprogression. This knowledge should be integrated into further efforts to implement imaging into BD clinical management.

TGR5-mediated lateral hypothalamus-dCA3-dorsolateral septum circuit regulates depressive-like behavior in male mice

Although bile acids play a notable role in depression, the pathological significance of the bile acid TGR5 membrane-type receptor in this disorder remains elusive. Using depression models of chronic social defeat stress and chronic restraint stress in male mice, we found that TGR5 in the lateral hypothalamic area (LHA) predominantly decreased in GABAergic neurons, the excitability of which increased in depressive-like mice. Upregulation of TGR5 or inhibition of GABAergic excitability in LHA markedly alleviated depressive-like behavior, whereas down-regulation of TGR5 or enhancement of GABAergic excitability facilitated stress-induced depressive-like behavior. TGR5 also bidirectionally regulated excitability of LHA GABAergic neurons via extracellular regulated protein kinases-dependent Kv4.2 channels. Notably, LHA GABAergic neurons specifically innervated dorsal CA3 (dCA3) CaMKIIα neurons for mediation of depressive-like behavior. LHA GABAergic TGR5 exerted antidepressant-like effects by disinhibiting dCA3 CaMKIIα neurons projecting to the dorsolateral septum (DLS). These findings advance our understanding of TGR5 and the LHAGABA→dCA3CaMKIIα→DLSGABA circuit for the development of potential therapeutic strategies in depression.

A multi-site 99mTc-HMPAO SPECT study of cerebral blood flow in a community sample of patients with major depression

Prior regional Cerebral Blood Flow (rCBF) studies in Major Depressive Disorder (MDD) have been limited by small, highly selective, non-representative samples that have yielded variable and poorly replicated findings. The aim of this study was to compare rCBF measures in a large, more representative community sample of adults with MDD and healthy control participants. This is a cross-sectional, retrospective multi-site cohort study in which clinical data from 338 patients 18-65 years of age with a primary diagnosis of MDD were retrieved from a central database for 8 privately owned, private-pay outpatient psychiatric centers across the United States. Two 99mTc-HMPAO SPECT brain scans, one at rest and one during performance of a continuous performance task, were acquired as a routine component of their initial clinical evaluation. In total, 103 healthy controls, 18-65 years old and recruited from the community were also assessed and scanned. Depressed patients had significantly higher rCBF in frontal, anterior cingulate, and association cortices, and in basal ganglia, thalamus, and cerebellum, after accounting for significantly higher overall CBF. Depression severity associated positively with rCBF in the basal ganglia, hippocampus, cerebellum, and posterior white matter. Elevated rCBF was especially prominent in women and older patients. Elevated rCBF likely represents pathogenic hypermetabolism in MDD, with its magnitude in direct proportion to depression severity. It is brain-wide, with disproportionate increases in cortical and subcortical attentional networks. Hypermetabolism may be a reasonable target for novel therapeutics in MDD.

Individualized Functional Brain System Topologies and Major Depression: Relationships Among Patch Sizes and Clinical Profiles and Behavior

BACKGROUND

Neuroimaging studies of major depression have typically been conducted using group-level approaches. However, given interindividual differences in brain systems, there is a need for individualized approaches to brain systems mapping and putative links toward diagnosis, symptoms, and behavior.

METHODS

We used an iterative parcellation approach to map individualized brain systems in 328 participants from a multisite, placebo-controlled clinical trial. We hypothesized that participants with depression would show abnormalities in salience, control, default, and affective systems, which would be associated with higher levels of self-reported anhedonia, anxious arousal, and worse cognitive performance. Within hypothesized brain systems, we compared patch sizes (number of vertices) between depressed and healthy control groups. Within depressed groups, abnormal patches were correlated with hypothesized clinical and behavioral measures.

RESULTS

Significant group differences emerged in hypothesized patches of 1) the lateral salience system (parietal operculum; t326 = -3.11, p = .002) and 2) the control system (left medial posterior prefrontal cortex region; z = -3.63, p < .001), with significantly smaller patches in these regions in participants with depression than in healthy control participants. Results suggest that participants with depression with significantly smaller patch sizes in the lateral salience system and control system regions experience greater anxious arousal and cognitive deficits.

CONCLUSIONS

The findings imply that neural features mapped at the individual level may relate meaningfully to diagnosis, symptoms, and behavior. There is strong clinical relevance in taking an individualized brain systems approach to mapping neural functional connectivity because these associated region patch sizes may help advance our understanding of neural features linked to psychopathology and foster future patient-specific clinical decision making.

Effects of childhood maltreatment and major depressive disorder on functional connectivity in hippocampal subregions

Major Depressive Disorder (MDD) with childhood maltreatment is a prevalent clinical phenotype. Prior studies have observed abnormal hippocampal activity in MDD patients, considering the hippocampus as a single nucleus. However, there is limited research investigating the static and dynamic changes in hippocampal subregion functional connectivity (FC) in MDD patients with childhood maltreatment. Therefore, we employed static and dynamic FC analyses using hippocampal subregions, including the anterior hippocampus and posterior hippocampus, as seed regions to investigate the neurobiological alterations associated with MDD resulting from childhood maltreatment. This study involved four groups: MDD with (n = 48) and without childhood maltreatment (n = 30), as well as healthy controls with (n = 57) and without (n = 46) childhood maltreatment. Compared to MDD patients without childhood maltreatment, those with childhood maltreatment exhibit altered FC between the hippocampal subregion and multiple brain regions, including the anterior cingulate gyrus, superior frontal gyrus, putamen, calcarine gyrus, superior temporal gyrus, angular gyrus, and supplementary motor area. Additionally, dynamic FC between the right medial-2 hippocampal head and the right calcarine gyrus shows a positive correlation with childhood maltreatment across all its subtypes. Moreover, dFC between the right hippocampal tail and the left angular gyrus moderates the relationship between childhood maltreatment and the depression severity. Our findings of distinct FC patterns within hippocampal subregions provide new clues for understanding the neurobiological basis of MDD with childhood maltreatment.

Structural and functional brain alterations in subthreshold depression: A multimodal coordinate-based meta-analysis

Imaging studies of subthreshold depression (StD) have reported structural and functional abnormalities in a variety of spatially diverse brain regions. However, there is no consensus among different studies. In the present study, we applied a multimodal meta-analytic approach, the Activation Likelihood Estimation (ALE), to test the hypothesis that StD exhibits spatially convergent structural and functional brain abnormalities compared to healthy controls. A total of 31 articles with 25 experiments were included, collectively representing 1001 subjects with StD. We found consistent differences between StD and healthy controls mainly in the left insula across studies with various neuroimaging methods. Further exploratory analyses found structural atrophy and decreased functional activities in the right pallidum and thalamus in StD, and abnormal spontaneous activity converged to the middle frontal gyrus. Coordinate-based meta-analysis found spatially convergent structural and functional impairments in StD. These findings provide novel insights for understanding the neural underpinnings of subthreshold depression and enlighten the potential targets for its early screening and therapeutic interventions in the future.

The relationship between the size and asymmetry of the lateral ventricles and cortical myelin content in individuals with mood disorders

Background

Although enlargement of the lateral ventricles was previously observed in individuals with mood disorders, the link between ventricular size and asymmetry with other indices of brain structure remains underexplored. In this study, we examined the association of lateral ventricular size and asymmetry with cortical myelin content in individuals with bipolar (BD) and depressive (DD) disorders compared to healthy controls (HC).

Methods

Magnetic resonance imaging (MRI) was used to obtain T1w and T2w images from 149 individuals (age=27.7 (SD=6.1) years, 78% female, BD=38, DD=57, HC=54). Cortical myelin content was calculated using the T1w/T2w ratio. Elastic net regularized regression identified brain regions whose myelin content was associated with ventricular size and asymmetry. A post-hoc linear regression examined how participants' diagnosis, illness duration, and current level of depression moderated the relationship between the size and asymmetry of the lateral ventricles and levels of cortical myelin in the selected brain regions.

Results

Individuals with mood disorders had larger lateral ventricles than HC. Larger ventricles and lower asymmetry were observed in individuals with BD who had longer lifetime illness duration and more severe current depressive symptoms. A greater left asymmetry was observed in participants with DD than in those with BD (p<0.01). Elastic net revealed that both ventricular enlargement and asymmetry were associated with altered myelin content in cingulate, frontal, and sensorimotor cortices. In BD, but not other groups, ventricular enlargement was related to altered myelin content in the right insular regions.

Conclusions

Lateral ventricular enlargement and asymmetry are linked to myelin content imbalance, thus, potentially leading to emotional and cognitive dysfunction in mood disorders.

Predicting treatment outcome based on resting-state functional connectivity in internalizing mental disorders: A systematic review and meta-analysis

Predicting treatment outcome in internalizing mental disorders prior to treatment initiation is pivotal for precision mental healthcare. In this regard, resting-state functional connectivity (rs-FC) and machine learning have often shown promising prediction accuracies. This systematic review and meta-analysis evaluates these studies, considering their risk of bias through the Prediction Model Study Risk of Bias Assessment Tool (PROBAST). We examined the predictive performance of features derived from rs-FC, identified features with the highest predictive value, and assessed the employed machine learning pipelines. We searched the electronic databases Scopus, PubMed and PsycINFO on the 12th of December 2022, which resulted in 13 included studies. The mean balanced accuracy for predicting treatment outcome was 77% (95% CI: [72%- 83%]). rs-FC of the dorsolateral prefrontal cortex had high predictive value in most studies. However, a high risk of bias was identified in all studies, compromising interpretability. Methodological recommendations are provided based on a comprehensive exploration of the studies' machine learning pipelines, and potential fruitful developments are discussed.

Consistent abnormal activity in the putamen by dopamine modulation in Parkinson's disease: A resting-state neuroimaging meta-analysis

OBJECTIVE

This study aimed to elucidate brain areas mediated by oral anti-parkinsonian medicine that consistently show abnormal resting-state activation in PD and to reveal their functional connectivity profiles using meta-analytic approaches.

METHODS

Searches of the PubMed, Web of Science databases identified 78 neuroimaging studies including PD OFF state (PD-OFF) versus (vs.) PD ON state (PD-ON) or PD-ON versus healthy controls (HCs) or PD-OFF versus HCs data. Coordinate-based meta-analysis and functional meta-analytic connectivity modeling (MACM) were performed using the activation likelihood estimation algorithm.

RESULTS

Brain activation in PD-OFF vs. PD-ON was significantly changed in the right putamen and left inferior parietal lobule (IPL). Contrast analysis indicated that PD-OFF vs. HCs had more consistent activation in the right paracentral lobule, right middle frontal gyrus, right thalamus, left superior parietal lobule and right putamen, whereas PD-ON vs. HCs elicited more consistent activation in the bilateral middle temporal gyrus, left occipital gyrus, right inferior frontal gyrus and right caudate. MACM revealed coactivation of the right putamen in the direct contrast of PD-OFF vs. PD-ON. Subtraction analysis of significant coactivation clusters for PD-OFF vs. PD-ON with the medium of HCs showed effects in the sensorimotor, top-down control, and visual networks. By overlapping the MACM maps of the two analytical strategies, we demonstrated that the coactivated brain region focused on the right putamen.

CONCLUSIONS

The convergence of local brain regions and co-activation neural networks are involved the putamen, suggesting its potential as a specific imaging biomarker to monitor treatment efficacy.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD CRD42022304150].

Mechanisms Involved in the Link between Depression, Antidepressant Treatment, and Associated Weight Change

Major depressive disorder is a severe mood disorder associated with a marked decrease in quality of life and social functioning, accompanied by a risk of suicidal behavior. Therefore, seeking out and adhering to effective treatment is of great personal and society-wide importance. Weight changes associated with antidepressant therapy are often cited as the reason for treatment withdrawal and thus are an important topic of interest. There indeed exists a significant mechanistic overlap between depression, antidepressant treatment, and the regulation of appetite and body weight. The suggested pathomechanisms include the abnormal functioning of the homeostatic (mostly humoral) and hedonic (mostly dopaminergic) circuits of appetite regulation, as well as causing neuromorphological and neurophysiological changes underlying the development of depressive disorder. However, this issue is still extensively discussed. This review aims to summarize mechanisms linked to depression and antidepressant therapy in the context of weight change.

Genetic evidence suggests a genetic association between major depressive disorder and reduced cortical gray matter volume: A Mendelian randomization study and mediation analysis

BACKGROUND

Several studies have suggested an association between major depressive disorder (MDD) and abnormal brain structure. However, it is unclear whether MDD affects cortical gray matter volume, a common indicator of cognitive function. We aimed to determine whether MDD was associated with decreased cortical gray matter volume (GMV) through a Mendelian randomization (MR) study.

METHODS

We obtained summary genetic data from a study conducted by the Psychiatric Genomics Consortium, which recruited a total of 480,359 participants (135,458 cases and 344,901 controls). Genetic tools-single nucleotide polymorphisms (SNPs)-of MDD were extracted from the study and their effects on gray matter volumes of the cortex and total brain were evaluated in a large cohort from the UK Biobank (n = 8427). The effects of the SNPs were pooled using inverse variance weighted (IVW) analysis and further tested in several sensitivity analyses. We tested whether C-reactive protein (CRP) levels and interleukin-6 signaling were the mediators of the effects using a multivariate MR model.

RESULTS

Thirty-three SNPs were identified and adopted as genetic tools for predicting MDD. IVW analysis showed that MDD was associated with lower overall GMV (beta value -0.106, 95%CI -0.188 to -0.023, p = 0.011) in the frontal pole (left frontal pole, -0.152, 95%CI -0.177 to -0.127, p = 0.013; right frontal pole, -0.133, 95%CI -0.253 to -0.013, p = 0.028). Multivariate and mediation analysis showed that interleukin-6 was an important mediator of GMV reduction. Reverse causality analysis found no evidence that total GMV affected the risk of MDD, but showed that increased left precuneus cortex volume and left posterior cingulate cortex volume were associated with increased risk of MDD.

LIMITATIONS

Potential pleiotropic effects and overestimation of real-world effects. Key assumptions for MR analysis may not be satisfactorily met.

CONCLUSION

MDD was associated with a reduced GMV, and interleukin-6 might be a mediator of GMV reduction.

Systematic review and meta-analysis: multimodal functional and anatomical neural alterations in autism spectrum disorder

BACKGROUND

This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD).

METHODS

A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software.

RESULTS

A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences.

CONCLUSIONS

The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.

Distinctive intrinsic functional connectivity alterations of anterior cingulate cortex subdivisions in major depressive disorder: A systematic review and meta-analysis

Evidence of whether the intrinsic functional connectivity of anterior cingulate cortex (ACC) and its subregions is altered in major depressive disorder (MDD) remains inconclusive. A systematic review and meta-analysis were therefore performed on the whole-brain resting-state functional connectivity (rsFC) studies using the ACC and its subregions as seed regions in MDD, in order to draw more reliable conclusions. Forty-four ACC-based rsFC studies were included, comprising 25 subgenual ACC-based studies, 11 pregenual ACC-based studies, and 17 dorsal ACC-based studies. Specific alterations of rsFC were identified for each ACC subregion in patients with MDD, with altered rsFC of subgenual ACC in emotion-related brain regions, of pregenual ACC in sensorimotor-related regions, and of dorsal ACC in cognition-related regions. Furthermore, meta-regression analysis revealed a significant negative correlation between the pgACC-caudate hypoconnectivity and percentage of female patients in the study cohort. This meta-analysis provides robust evidence of altered intrinsic functional connectivity of the ACC subregions in MDD, which may hold relevance to understanding the origin of, and treating, the emotional, sensorimotor and cognitive dysfunctions that are often observed in these patients.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

An amygdala-centered effective connectivity network in trait anxiety

Previous studies have established that the amygdala plays an important role in trait anxiety. However, there remains limited knowledge regarding the changes in amygdala-centered effective connectivity network associated with this trait. The current study employed the Granger Causal analysis to investigate the directional connectivity patterns involving the amygdala in relation to trait anxiety in a large cohort of young adults (N = 424). The results revealed a negative association between trait anxiety scores and the Granger causality from the left middle frontal gyrus and right superior frontal gyrus to the right amygdala. Conversely, higher trait anxiety levels were found to be associated with increased effective connectivity from the left amygdala to the left hippocampus. These results demonstrated the significance of the prefrontal cortex-amygdala-hippocampus neural circuitry in the neurobiological mechanisms underlying trait anxiety. Our findings advance the comprehension of this characteristic, holding promise for informing strategies in the prevention and treatment of related mental disorders.

A Systematic Evaluation of Machine Learning-Based Biomarkers for Major Depressive Disorder

Importance

Biological psychiatry aims to understand mental disorders in terms of altered neurobiological pathways. However, for one of the most prevalent and disabling mental disorders, major depressive disorder (MDD), no informative biomarkers have been identified.

Objective

To evaluate whether machine learning (ML) can identify a multivariate biomarker for MDD.

Design, Setting, and Participants

This study used data from the Marburg-Münster Affective Disorders Cohort Study, a case-control clinical neuroimaging study. Patients with acute or lifetime MDD and healthy controls aged 18 to 65 years were recruited from primary care and the general population in Münster and Marburg, Germany, from September 11, 2014, to September 26, 2018. The Münster Neuroimaging Cohort (MNC) was used as an independent partial replication sample. Data were analyzed from April 2022 to June 2023.

Exposure

Patients with MDD and healthy controls.

Main Outcome and Measure

Diagnostic classification accuracy was quantified on an individual level using an extensive ML-based multivariate approach across a comprehensive range of neuroimaging modalities, including structural and functional magnetic resonance imaging and diffusion tensor imaging as well as a polygenic risk score for depression.

Results

Of 1801 included participants, 1162 (64.5%) were female, and the mean (SD) age was 36.1 (13.1) years. There were a total of 856 patients with MDD (47.5%) and 945 healthy controls (52.5%). The MNC replication sample included 1198 individuals (362 with MDD [30.1%] and 836 healthy controls [69.9%]). Training and testing a total of 4 million ML models, mean (SD) accuracies for diagnostic classification ranged between 48.1% (3.6%) and 62.0% (4.8%). Integrating neuroimaging modalities and stratifying individuals based on age, sex, treatment, or remission status does not enhance model performance. Findings were replicated within study sites and also observed in structural magnetic resonance imaging within MNC. Under simulated conditions of perfect reliability, performance did not significantly improve. Analyzing model errors suggests that symptom severity could be a potential focus for identifying MDD subgroups.

Conclusion and Relevance

Despite the improved predictive capability of multivariate compared with univariate neuroimaging markers, no informative individual-level MDD biomarker-even under extensive ML optimization in a large sample of diagnosed patients-could be identified.

Neuromelanin-sensitive magnetic resonance imaging in the study of mental disorder: A systematic review

Dopamine and norepinephrine are implicated in the pathophysiology of mental disorders, but non-invasive study of their neuronal function remains challenging. Recent research suggests that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) techniques may overcome this limitation by enabling the non-invasive imaging of the substantia nigra (SN)/ ventral tegmental area (VTA) dopaminergic and locus coeruleus (LC) noradrenergic systems. A review of 19 studies that met the criteria for NM-MRI application in mental disorders found that despite the use of heterogeneous sequence parameters and metrics, nearly all studies reported differences in contrast ratio (CNR) of LC or SN/VTA between patients with mental disorders and healthy controls. These findings suggest that NM-MRI is a valuable tool in psychiatry, but the differences in sequence parameters across studies hinder comparability, and a standardized analysis pipeline is needed to improve the reliability of results. Further research using standardized methods is needed to better understand the role of dopamine and norepinephrine in mental disorders.

The difference in volumetric alternations of the orbitofrontal-limbic-striatal system between major depressive disorder and anxiety disorders: A systematic review and voxel-based meta-analysis

BACKGROUND

Major depressive disorder (MDD) and anxiety disorders (ANX) are psychiatric disorders with high mutual comorbidity rates that might indicate some shared neurobiological pathways between them, but they retain diverse phenotypes that characterize themselves specifically. However, no consistent evidence exists for common and disorder-specific gray matter volume (GMV) alternations between them.

METHODS

A systematic review and meta-analysis on voxel-based morphometry studies of patients with MDD and ANX were performed. The effect of comorbidity was explicitly controlled during disorder-specific analysis and particularly investigated in patient with comorbidity.

RESULTS

A total of 45 studies with 54 datasets comprising 2196 patients and 2055 healthy participants met the inclusion criteria. Deficits in the orbitofrontal cortex, striatum, and limbic regions were found in MDD and ANX. The disorder-specific analyses showed decreased GMV in the bilateral anterior cingulate cortex, right striatum, hippocampus, and cerebellum in MDD, while decreased GMV in the left striatum, amygdala, insula, and increased cerebellar volume in ANX. A totally different GMV alternation pattern was shown involving bilateral temporal and parietal gyri and left fusiform gyrus in patients with comorbidity.

LIMITATIONS

Owing to the design of included studies, only partial patients in the comorbid group had a secondary comorbidity diagnosis.

CONCLUSION

Patients with MDD and ANX shared a structural disruption in the orbitofrontal-limbic-striatal system. The disorder-specific effects manifested their greatest severity in distinct lateralization and directionality of these changes that differentiate MDD from ANX. The comorbid group showed a totally different GMV alternation pattern, possibly suggesting another illness subtype that requires further investigation.

A distinctive subcortical functional connectivity pattern linking negative affect and treatment outcome in major depressive disorder

Major depressive disorder (MDD) is associated with functional disturbances in subcortical regions. In this naturalistic prospective study (NCT03294525), we aimed to investigate relationships among subcortical functional connectivity (FC), mood symptom profiles and treatment outcome in MDD using multivariate methods. Medication-free participants with MDD (n = 135) underwent a functional magnetic resonance imaging scan at baseline and completed posttreatment clinical assessment after 8 weeks of antidepressant monotherapy. We used partial least squares (PLS) correlation analysis to explore the association between subcortical FC and mood symptom profiles. FC score, reflecting the weighted representation of each individual in this association, was computed. Replication analysis was undertaken in an independent sample (n = 74). We also investigated the relationship between FC score and treatment outcome in the main sample. A distinctive subcortical connectivity pattern was found to be associated with negative affect. In general, higher FC between the caudate, putamen and thalamus was associated with greater negative affect. This association was partly replicated in the independent sample (similarity between the two samples: r = 0.66 for subcortical connectivity, r = 0.75 for mood symptom profile). Lower FC score predicted both remission and response to treatment after 8 weeks of antidepressant monotherapy. The emphasis here on the role of dorsal striatum and thalamus consolidates prior work of subcortical connectivity in MDD. The findings provide insight into the pathogenesis of MDD, linking subcortical FC with negative affect. However, while the FC score significantly predicted treatment outcome, the low odds ratio suggests that finding predictive biomarkers for depression remains an aspiration.

Capturing the Individual Deviations From Normative Models of Brain Structure for Depression Diagnosis and Treatment

BACKGROUND

The high heterogeneity of depression prevents us from obtaining reproducible and definite anatomical maps of brain structural changes associated with the disorder, which limits the individualized diagnosis and treatment of patients. In this study, we investigated the clinical issues related to depression according to individual deviations from normative ranges of gray matter volume.

METHODS

We enrolled 1092 participants, including 187 patients with depression and 905 healthy control participants. Structural magnetic resonance imaging data of healthy control participants from the Human Connectome Project (n = 510) and REST-meta-MDD Project (n = 229) were used to establish a normative model across the life span in adults 18 to 65 years old for each brain region. Deviations from the normative range for 187 patients and 166 healthy control participants recruited from two local hospitals were captured as normative probability maps, which were used to identify the disease risk and treatment-related latent factors.

RESULTS

In contrast to case-control results, our normative modeling approach revealed highly individualized patterns of anatomic abnormalities in depressed patients (less than 11% extreme deviation overlapping for any regions). Based on our classification framework, models trained with individual normative probability maps (area under the receiver operating characteristic curve range, 0.7146-0.7836) showed better performance than models trained with original gray matter volume values (area under the receiver operating characteristic curve range, 0.6800-0.7036), which was verified in an independent external test set. Furthermore, different latent brain structural factors in relation to antidepressant treatment were revealed by a Bayesian model based on normative probability maps, suggesting distinct treatment response and inclination.

CONCLUSIONS

Capturing personalized deviations from a normative range could help in understanding the heterogeneous neurobiology of depression and thus guide clinical diagnosis and treatment of depression.

Personalized connectivity-based network targeting model of transcranial magnetic stimulation for treatment of psychiatric disorders: computational feasibility and reproducibility

Repetitive transcranial magnetic stimulation (rTMS) holds promise for treating psychiatric disorders; however, the variability in treatment efficacy among individuals underscores the need for further improvement. Growing evidence has shown that TMS induces a broad network modulatory effect, and its effectiveness may rely on accurate modulation of the pathological network specific to each disorder. Therefore, determining the optimal TMS coil setting that will engage the functional pathway delivering the stimulation is crucial. Compared to group-averaged functional connectivity (FC), individual FC provides specific information about a person's brain functional architecture, offering the potential for more accurate network targeting for personalized TMS. However, the low signal-to-noise ratio (SNR) of FC poses a challenge when utilizing individual resting-state FC. To overcome this challenge, the proposed solutions include increasing the scan duration and employing the cluster method to enhance the stability of FC. This study aimed to evaluate the stability of a personalized FC-based network targeting model in individuals with major depressive disorder or schizophrenia with auditory verbal hallucinations. Using resting-state functional magnetic resonance imaging data from the Human Connectome Project, we assessed the model's stability. We employed longer scan durations and cluster methodologies to improve the precision in identifying optimal individual sites. Our findings demonstrate that a scan duration of 28 minutes and the utilization of the cluster method achieved stable identification of individual sites, as evidenced by the intraindividual distance falling below the ~1cm spatial resolution of TMS. The current model provides a feasible approach to obtaining stable personalized TMS targets from the scalp, offering a more accurate method of TMS targeting in clinical applications.

Lifetime Exposure to Depression and Neuroimaging Measures of Brain Structure and Function

Importance

Despite decades of neuroimaging studies reporting brain structural and functional alterations in depression, discrepancies in findings across studies and limited convergence across meta-analyses have raised questions about the consistency and robustness of the observed brain phenotypes.

Objective

To investigate the associations between 6 operational criteria of lifetime exposure to depression and functional and structural neuroimaging measures.

Design, Setting, and Participants

This cross-sectional study analyzed data from a UK Biobank cohort of individuals aged 45 to 80 years who were enrolled between January 1, 2014, and December 31, 2018. Participants included individuals with a lifetime exposure to depression and matched healthy controls without indications of psychosis, mental illness, behavior disorder, and disease of the nervous system. Six operational criteria of lifetime exposure to depression were evaluated: help seeking for depression; self-reported depression; antidepressant use; depression definition by Smith et al; hospital International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) diagnosis codes F32 and F33; and Composite International Diagnostic Interview Short Form score. Six increasingly restrictive depression definitions and groups were defined based on the 6 depression criteria, ranging from meeting only 1 criterion to meeting all 6 criteria. Data were analyzed between January and October 2022.

Main Outcomes and Measures

Functional measures were calculated using voxel-wise fractional amplitude of low-frequency fluctuation (fALFF), global correlation (GCOR), and local correlation (LCOR). Structural measures were calculated using gray matter volume (GMV).

Results

The study included 20 484 individuals with lifetime depression (12 645 females [61.7%]; mean [SD] age, 63.91 [7.60] years) and 25 462 healthy controls (14 078 males [55.3%]; mean [SD] age, 65.05 [7.8] years). Across all depression criteria, individuals with lifetime depression displayed regionally consistent decreases in fALFF, LCOR, and GCOR (Cohen d range, -0.53 [95% CI, -0.88 to -0.15] to -0.04 [95% CI, -0.07 to -0.01]) but not in GMV (Cohen d range, -0.47 [95 % CI, -0.75 to -0.12] to 0.26 [95% CI, 0.15-0.37]). Hospital ICD-10 diagnosis codes F32 and F33 (median [IQR] difference in effect sizes, -0.14 [-0.17 to -0.11]) and antidepressant use (median [IQR] difference in effect sizes, -0.12 [-0.16 to -0.10]) were criteria associated with the most pronounced alterations.

Conclusions and Relevance

Results of this cross-sectional study indicate that lifetime exposure to depression was associated with robust functional changes, with a more restrictive depression definition revealing more pronounced alterations. Different inclusion criteria for depression may be associated with the substantial variation in imaging findings reported in the literature.

The anterior cingulate cortex controls the hyperactivity in subthalamic neurons in male mice with comorbid chronic pain and depression

Neurons in the subthalamic nucleus (STN) become hyperactive following nerve injury and promote pain-related responses in mice. Considering that the anterior cingulate cortex (ACC) is involved in pain and emotion processing and projects to the STN, we hypothesize that ACC neurons may contribute to hyperactivity in STN neurons in chronic pain. In the present study, we showed that ACC neurons enhanced activity in response to noxious stimuli and to alterations in emotional states and became hyperactive in chronic pain state established by spared nerve injury of the sciatic nerve (SNI) in mice. In naïve mice, STN neurons were activated by noxious stimuli, but not by alterations in emotional states. Pain responses in STN neurons were attenuated in both naïve and SNI mice when ACC neurons were inhibited. Furthermore, optogenetic activation of the ACC-STN pathway induced bilateral hyperalgesia and depression-like behaviors in naive mice; conversely, inhibition of this pathway is sufficient to attenuate hyperalgesia and depression-like behaviors in SNI mice and naïve mice subjected to stimulation of STN neurons. Finally, mitigation of pain-like and depression-like behaviors in SNI mice by inhibition of the ACC-STN projection was eliminated by activation of STN neurons. Our results demonstrate that hyperactivity in the ACC-STN pathway may be an important pathophysiology in comorbid chronic pain and depression. Thus, the ACC-STN pathway may be an intervention target for the treatment of the comorbid chronic pain and depression.

A multimodal meta-analysis of regional functional and structural brain abnormalities in obsessive-compulsive disorder

Numerous neuroimaging studies of resting-state functional imaging and voxel-based morphometry (VBM) have revealed abnormalities in specific brain regions in obsessive-compulsive disorder (OCD), but results have been inconsistent. We conducted a whole-brain voxel-wise meta-analysis on resting-state functional imaging and VBM studies that investigated differences of functional activity and gray matter volume (GMV) between patients with OCD and healthy controls (HCs) using seed-based d mapping (SDM) software. A total of 41 independent studies (51 datasets) for resting-state functional imaging and 42 studies (46 datasets) for VBM were included by a systematic literature search. Overall, patients with OCD displayed increased spontaneous functional activity in the bilateral inferior frontal gyrus (IFG) (extending to the bilateral insula) and bilateral medial prefrontal cortex/anterior cingulate cortex (mPFC/ACC), as well as decreased spontaneous functional activity in the bilateral paracentral lobule, bilateral cerebellum, left caudate nucleus, left inferior parietal gyri, and right precuneus cortex. For the VBM meta-analysis, patients with OCD displayed increased GMV in the bilateral thalamus (extending to the bilateral cerebellum), right striatum, and decreased GMV in the bilateral mPFC/ACC and left IFG (extending to the left insula). The conjunction analyses found that the bilateral mPFC/ACC, left IFG (extending to the left insula) showed decreased GMV with increased intrinsic function in OCD patients compared to HCs. This meta-analysis demonstrated that OCD exhibits abnormalities in both function and structure in the bilateral mPFC/ACC, insula, and IFG. A few regions exhibited only functional or only structural abnormalities in OCD, such as the default mode network, striatum, sensorimotor areas, and cerebellum. It may provide useful insights for understanding the underlying pathophysiology of OCD and developing more targeted and efficacious treatment and intervention strategies.

Neuroplasticity of the left dorsolateral prefrontal cortex in patients with treatment-resistant depression as indexed with paired associative stimulation: a TMS-EEG study

Major depressive disorder affects over 300 million people globally, with approximately 30% experiencing treatment-resistant depression (TRD). Given that impaired neuroplasticity underlies depression, the present study focused on neuroplasticity in the dorsolateral prefrontal cortex (DLPFC). Here, we aimed to investigate the differences in neuroplasticity between 60 individuals with TRD and 30 age- and sex-matched healthy controls (HCs). To induce neuroplasticity, participants underwent a paired associative stimulation (PAS) paradigm involving peripheral median nerve stimulation and transcranial magnetic stimulation (TMS) targeting the left DLPFC. Neuroplasticity was assessed by using measurements combining TMS with EEG before and after PAS. Both groups exhibited significant increases in the early component of TMS-evoked potentials (TEP) after PAS (P < 0.05, paired t-tests with the bootstrapping method). However, the HC group demonstrated a greater increase in TEPs than the TRD group (P = 0.045, paired t-tests). Additionally, event-related spectral perturbation analysis highlighted that the gamma power significantly increased after PAS in the HC group, whereas it was decreased in the TRD group (P < 0.05, paired t-tests with the bootstrapping method). This gamma power modulation revealed a significant group difference (P = 0.006, paired t-tests), indicating an inverse relationship for gamma power modulation. Our findings underscore the impaired neuroplasticity of the DLPFC in individuals with TRD.

Impaired visual-motor functional connectivity in first-episode medication-naïve patients with major depressive disorder

The perceptual dysfunctions have been fundamental causes of cognitive and emotional problems in patients with major depressive disorder. However, visual system impairment in depression has been underexplored. Here, we explored functional connectivity in a large cohort of first-episode medication-naïve patients with major depressive disorder (n = 190) and compared it with age- and sex-matched healthy controls (n = 190). A recently developed individual-oriented approach was applied to parcellate the cerebral cortex into 92 regions of interest using resting-state functional magnetic resonance imaging data. Significant reductions in functional connectivities were observed between the right lateral occipitotemporal junction within the visual network and 2 regions of interest within the sensorimotor network in patients. The volume of right lateral occipitotemporal junction was also significantly reduced in major depressive disorder patients, indicating that this visual region is anatomically and functionally impaired. Behavioral correlation analysis showed that the reduced functional connectivities were significantly associated with inhibition control in visual-motor processing in patients. Taken together, our data suggest that functional connectivity between visual network and sensorimotor network already shows a significant reduction in the first episode of major depressive disorder, which may interfere with the inhibition control in visual-motor processing. The lateral occipitotemporal junction may be a hub of disconnection and may play a role in the pathophysiology of major depressive disorder.