White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

Oligodendroglia Are Primed for Antigen Presentation in Response to Chronic Stress-Induced Microglial-Derived Inflammation

Chronic stress is a major contributor to the development of major depressive disorder, one of the leading causes of disability worldwide. Using a model of repeated social defeat stress in mice, we and others have reported that neuroinflammation plays a dynamic role in the development of behavioral deficits consistent with social avoidance and impaired reward responses. Animals susceptible to the model also exhibit hypomyelination in the medial prefrontal cortex, indicative of changes in the differentiation pathway of cells of the oligodendroglial lineage (OLN). We computationally confirmed the presence of immune oligodendrocytes, a population of OLN cells, which express immune markers and myelination deficits. In the current study, we report that microglia are necessary to induce expression of antigen presentation markers (and other immune markers) on oligodendroglia. We further associate the appearance of these markers with changes in the OLN and confirm that microglial changes precede OLN changes. Using co-cultures of microglia and OLN, we show that under inflammatory conditions the processes of phagocytosis and expression of MHCII are linked, suggesting potential priming for antigen presentation by OLN cells. Our findings provide insights into the nature of these OLN cells with immune capabilities, their obligatory interaction with microglia, and identify them as a potential cellular contributor to the pathological manifestations of psychosocial stress.

Gamma oscillations as correlates of depression: updating Fitzgerald and Watson (2018)

Depression remains one of the most common and debilitating neuropsychiatric conditions, with little consistency in treatment efficacy. Some of the lack of success in developing effective treatments has been the absence of a reliable biomarker of depression, despite many attempts. One such potential biomarker is the electrical activity of the brain that occurs in the gamma band (30-200 Hz). To evaluate the state of research into gamma as a biomarker of depression, a review of recent research literature was conducted. A total of 31 relevant papers was identified, 22 of which used resting-state studies, and nine included a stimulus-task. These studies were examined here in terms of their definition of gamma, sample sizes, research focus, brain region examined, and EEG methodologies used. Due to the range of methodologies, some inconsistent results emerged but several valuable findings remained, including that depressed patients usually had higher gamma power than their healthy controls (HC), that the imposition of a perceptual task into the research protocol also introduced a strong element of confound to the results, and that studies that sought to evaluate the role of gamma in treatment were yet to be established as reliable. Key issues for future research are discussed, and the potential for gamma as a biomarker of depression is evaluated as emerging.

Longitudinal associations between white matter integrity, early life adversities, and treatment response following cognitive-behavioral therapy in depression

Cognitive-behavioral therapy (CBT) is a primary treatment for depression. Although previous research has underscored the significant roles of white matter (WM) alterations and maladaptive parenting in depression risk, their associations with CBT response remain largely unknown. This longitudinal study investigated the interplay of WM integrity changes over time, treatment response, and parenting style in patients with depression. Diffusion-tensor-imaging and clinical data were assessed in n = 65 (55% female) patients with depression before and after 20 CBT sessions and n = 65 (68% female) healthy controls (HC) in a naturalistic design. Linear-mixed-effect models compared changes in fractional anisotropy (FA) between groups and tested associations between FA changes and symptom changes. It was investigated whether parenting style predicts depressive symptoms at follow-up and whether FA changes mediate this association. Patients showed differential FA changes over time in the corpus callosum and corona radiata compared to HC (ptfce-FWE = 0.008). Increases in FA in the corpus callosum, corona radiata and superior longitudinal fasciculus were linked to symptom improvement after CBT in patients (ptfce-FWE = 0.023). High parental care (pFDR = 0.010) and low maternal overprotection (pFDR = 0.001) predicted fewer depressive symptoms at follow-up. The association between maternal overprotection and depressive symptoms at follow-up was mediated by FA changes (pFDR = 0.044). Robustness checks-controlling for outliers, non-linear age effects, clinical characteristics, and patient subgroups-supported these results. Overall, patients with depression show changes in WM integrity following CBT, which are linked to treatment response. The results highlight the significance of early life adversities and related microstructural changes in the effectiveness of CBT for treating depression.

Disrupted interhemispheric functional and structural connectivity in patients with major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is associated with disrupted interhemispheric cooperation. However, the relationship between structural and functional alterations in interhemispheric cooperation in patients with MDD remains unclear. We investigated the associations between voxel-mirrored homotopic connectivity (VMHC) and radial diffusivity (RD) within the corpus callosum (CC) and their links to depressive symptoms in patients with MDD.

METHODS

Sixty patients with MDD and 38 healthy controls (HCs) were assessed using resting-state functional MRI (rs-fMRI) and diffusion MRI (dMRI) to evaluate interhemispheric functional connectivity (VMHC) and structural integrity (RD) in the CC subregions. Group comparisons, correlation analyses, and mediation analyses were conducted to identify the significant differences, relationships, and indirect effects.

RESULTS

Patients with MDD showed significantly reduced VMHC in the bilateral postcentral gyrus and lingual gyrus and increased RD in the CC subregions CC3, CC4, and CC5, indicating impaired functional and structural connectivity. Lower VMHC in the lingual gyrus was negatively correlated with depressive severity, whereas increased RD in the CC4 and CC5 was positively correlated with depressive symptoms. Mediation analysis revealed that the VMHC in the lingual gyrus fully mediated the relationship between RD in CC5 and depressive symptoms, suggesting a pathway through which structural impairments may affect mood through abnormal functional connectivity.

LIMITATIONS

The cross-sectional design limits the assessment of changes over time, and focusing solely on interhemispheric connectivity may overlook other networks involved in MDD.

CONCLUSION

These findings provide preliminary evidence for disrupted interhemispheric coordination in MDD, with both functional and structural connectivity impairments linked to depressive symptoms. The mediating effect of the VMHC in the lingual gyrus highlights the potential role of interhemispheric connectivity in the pathophysiology of MDD. Our results provide an integrative perspective on the functional and microstructural organization of the brain in patients with MDD.

Lifetime depression, sleep disruption and brain structure in the UK Biobank cohort

Whether depression and poor sleep interact or have statistically independent associations with brain structure and its change over time is not known. Within a subset of UK Biobank participants with neuroimaging and subjective and/or objective sleep data (n = 28,351), we examined associations between lifetime depression and sleep disruption, and their interaction with structural neuroimaging measures, both cross-sectionally and longitudinally. Sleep variables were: self-reported insomnia and difficulty getting up; actigraphy-derived short sleep (<7 h); sustained inactivity bouts during daytime (SIBD); and sleep efficiency. Imaging measures were white matter microstructure, subcortical volumes, cortical thickness and surface area of 24 cortical regions of interest. Individuals with lifetime depression (self-reported, mental health questionnaire or health records) were contrasted with healthy controls. Interactions between depression and difficulty getting up for i) right nucleus accumbens volume and ii) mean diffusivity of forceps minor, reflected a larger negative association of poor sleep in the presence vs. absence of depression. Depression was associated with widespread reductions in white matter integrity. Depression, higher SIBD and difficulty getting up were individually associated with smaller cortical volumes and surface area, particularly in the frontal and parietal lobes. Many regions showed age-related decline, but this was not exacerbated by either depression or sleep disturbance. Overall, we identified widespread cross-sectional associations of both lifetime depression and sleep measures with brain structure. Findings were more consistent with additive rather than synergistic effects - although in some regions we observed greater magnitude of deleterious associations from poor sleep phenotypes in the presence of depression.

Advancing the diagnosis of major depressive disorder: Integrating neuroimaging and machine learning

Major depressive disorder (MDD), a psychiatric disorder characterized by functional brain deficits, poses considerable diagnostic and treatment challenges, especially in adolescents owing to varying clinical presentations. Biomarkers hold substantial clinical potential in the field of mental health, enabling objective assessments of physiological and pathological states, facilitating early diagnosis, and enhancing clinical decision-making and patient outcomes. Recent breakthroughs combine neuroimaging with machine learning (ML) to distinguish brain activity patterns between MDD patients and healthy controls, paving the way for diagnostic support and personalized treatment. However, the accuracy of the results depends on the selection of neuroimaging features and algorithms. Ensuring privacy protection, ML model accuracy, and fostering trust are essential steps prior to clinical implementation. Future research should prioritize the establishment of comprehensive legal frameworks and regulatory mechanisms for using ML in MDD diagnosis while safeguarding patient privacy and rights. By doing so, we can advance accuracy and personalized care for MDD.

Repeated intermittent administration of 3,4-methylenedioxymethamphetamine mitigates demyelination in the brain from cuprizone-treated mice

3,4-Methylenedioxymethamphetamine (MDMA), commonly known as a recreational drug, may also offer therapeutic benefits for mental health. Population-based studies suggest that MDMA users have a lower risk of demyelinating diseases, such as depression. Given the role of the gut microbiota in mediating MDMA's effects, we hypothesized that MDMA might confer mental health benefits via the gut-brain axis. Cuprizone (CPZ) induces demyelination by chelating copper, which leads to oligodendrocyte death and subsequent myelin loss. This study investigated the impact of MDMA on brain demyelination in CPZ-treated mice, focusing on the gut-brain axis. Repeated intermittent MDMA administration (10 mg/kg, three times weekly for 6 weeks) significantly reduced demyelination in the corpus callosum (CC) of CPZ-treated mice. Gut microbiota and non-targeted metabolomics analyses revealed notable differences in specific gut bacteria and plasma (β-D-allose and L-sorbose) or fecal metabolite (carnitine) levels between MDMA-treated and vehicle-treated CPZ-exposed mice. Negative correlations were found between the levels of metabolites (β-D-allose, L-sorbose, and carnitine) and the relative abundance of Romboutsia and Romboutsia timonensis. These findings suggest that intermittent MDMA administration may alleviate demyelination in the CC of CPZ-treated mice via the gut-brain axis. Further research is needed to elucidate the roles of gut microbiota and metabolites in MDMA's effects on brain demyelination and to investigate other demyelination models.

Effect of continuous esketamine infusion on brain white matter microstructure in patients with major depression: A diffusion tensor imaging study

INTRODUCTION

Esketamine has demonstrated acute antidepressant effects in patients with major depressive disorder (MDD). This study investigated whether these effects associate with reversible white matter fiber integrity recovery using diffusion imaging.

METHOD

Twenty patients with MDD and 20 healthy controls received 2-week esketamine treatment. Patients received 0.25 mg/kg intravenous esketamine. Emotional and cognitive recovery were assessed. Diffusion tensor imaging and tract-based spatial statistics evaluated white matter fiber integrity pre/post-treatment. Correlation analyses examined associations between white matter changes and clinical scales.

RESULTS

Compared to controls, patients with MDD exhibited decreased fractional anisotropy (FA) values of cerebral white matter fibers involving the association fibers, the commissural fibers and projection fibers. Esketamine effectively reduced depression, anxiety, and suicidal ideation scores while improving cognitive function. However, no reversible recovery of compromised white matter integrity was observed after 2 weeks of esketamine treatment. FA reductions in projection fibers correlated with anxiety and suicidal ideation severity.

LIMITATIONS

Concurrent sertraline use and lack of placebo control limited our ability to isolate esketamine's effects. The wide age range may have introduced response variability. We used minimal effective dosages based on previous research. The small sample size limited statistical power. Larger, more controlled studies are needed to validate these preliminary findings.

DISCUSSION

This study enhances MDD neuropathological understanding, with widespread white matter impairment and associations between projection fibers and symptom severity. While producing significant antidepressant effects, short-term esketamine did not recover compromised white matter microstructure.

Abnormal neuritic microstructures in the anterior limb of internal capsules in treatment-resistant depression - A cross-sectional NODDI study

BACKGROUND

Microstructural deficits of brain tissue are implicated in the pathophysiology of major depressive disorder (MDD). Recent studies have highlighted the neurotrophic mechanisms underlying effective treatments such as ketamine for treatment-resistant depression (TRD). However, little is known about microstructural changes in TRD. Neurite orientation dispersion and density imaging (NODDI) has enabled in vivo investigation of gray matter (GM) and white matter (WM) microstructure. This study sought to examine microstructural abnormalities in gray and white matter in patients with TRD using NODDI.

METHODS

This study compared the neurite density index (NDI) and orientation dispersion index (ODI) of neurites in 70 patients with TRD and 35 healthy controls. We fitted separate optimal NODDI models for gray and white matter. The locations of microstructural deficit were identified using region-based and voxel-based analysis. The affected white matter fibers were tracked with correlational tractography analysis.

RESULTS

An increase of ODI at the middle to the ventral part of the right anterior limb of the internal capsule (ALIC) was observed in patients with TRD compared with healthy controls. The quantitative anisotropy of frontothalamic fibers passing through the ALIC negatively correlated with the ODI increase in the TRD group.

CONCLUSION

The microstructural disorganization of the frontothalamic pathway could be linked to the pathophysiology and individual heterogeneity of TRD.

Blood cytokines in major depressive disorder in drug-naïve adolescents: A systematic review and meta-analysis

BACKGROUND

Major depressive disorder (MDD) is the most common mental health problem worldwide. Increased levels of inflammation are associated with MDD, though this relationship has been suggested to be bidirectional. The first incidence of a depressive episode usually occurs during adolescence. Hence, examining depressed, drug-naïve adolescents is important to understand the role of inflammation in the pathophysiology of MDD. Cytokines might play a crucial role in inflammation associated with MDD. Therefore, this article aims to investigate the changes in the levels of peripheral blood cytokines in adolescents with MDD.

METHODS

We conducted a systematic review and meta-analysis to assess the changes in peripheral blood cytokines in drug-naïve adolescents (10-18 years) with MDD. A comprehensive search across four databases was performed to identify original research articles. Studies in which the diagnosis of MDD was set by semi-structured interview were included.

RESULTS

Of 2291 articles, 12 met the inclusion criteria for the review, with seven suitable for meta-analysis & including up to five studies per cytokine. The meta-analysis revealed significant associations between tumor necrosis factor (TNF)-α (n = 222, Hedge's g = 0.51, p <0.01) and MDD in adolescents compared to healthy individuals. However, other blood cytokines, including interleukin (IL)-1β, IL-4, IL-6, IL-8, and interferon (IFN)-γ, did not significantly correlate with MDD in adolescents.

CONCLUSION

TNF-α was significantly elevated in drug-naïve adolescents with MDD. To further understand the role of TNF-α in MDD, a thorough investigation is required, taking into account the diversity, subtypes, chronicity, and severity of MDD.

Microstructure Abnormalities of Diffusion Tensor Imaging Measures in First-Episode, Treatment-Naïve Adolescents With Major Depressive Disorder: An Integrated AFQ and TBSS Study

PURPOSE

Structural changes during depressive episodes in adolescents with major depressive disorder (MDD) remains unclear due to participant heterogeneity, illness chronicity, and medication confounders. This study aimed to explore white matter (WM) microstructural changes in first-episode, treatment-naïve adolescents with MDD using an integrated diffusion tensor imaging (DTI) approach.

METHOD

We recruited 66 subjects, including 37 adolescents with MDD and 29 healthy controls. Two main DTI techniques, automated fiber quantification (AFQ) and tract-based spatial statistics (TBSS), were used to analyze fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD), and mean diffusivity (MD) in WM tracts. DTI measures were then correlated with the depressive symptoms evaluated by Hamilton Depression Rating Scale scores (HAMD-17).

FINDINGS

In AFQ, MDD patients showed significant segmental differences in WM tracts compared to controls, including a negative correlation between SLF AD values and depression severity. TBSS revealed reduced FA in the cingulum, forceps minor, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, SLF, and uncinate fasciculus in MDD.

CONCLUSION

Our integrated DTI analysis in a unique first-episode, medication-naïve cohort revealed microstructural changes in adolescent MDD not previously reported. These findings may provide imaging markers for early detection and enhance our understanding of depression pathology in youth.

Distinguished multimodal imaging features affected by COVID-19 in major depressive disorder patients

OBJECTIVES

Growing attention has been directed toward the structural and functional alterations among individuals infected with COVID-19. However, data on its impact on patients with Major Depressive Disorder (MDD) remain limited.

METHODS

This study investigates the effects of COVID-19 on patients with MDD and healthy controls (HCs) using MRI scans. Participants were categorized into four groups: MDD patients before (n = 165) and after COVID-19 infection (n = 70), HCs before (n = 108) and after COVID-19 infection (n = 57). All participants underwent T1-weighted imaging, diffusion tensor imaging (DTI), and resting-state functional MRI from January 2022 to August 2023.

RESULTS

Structural alterations associated with COVID-19 were predominantly observed in the white matter (WM) rather than the gray matter (GM), with specific involvement noted in the superior longitudinal fasciculus tract, Forceps minor tract, and cingulum-cingulate gyrus tract among patients with MDD. Functional changes were spread from GM to WM. The bilateral supplementary motor area, the left angular gyrus, the left subcortical regions (amygdala and parahippocampal gyrus), and various WM tracts showed significant infection-related changes across groups.

CONCLUSION

COVID-19 infection induces significant microstructural damage of WM in healthy individuals and exacerbates white matter microstructural injury of MDD. These findings suggest that WM might be more susceptible to COVID-19 effects than GM in both MDD patients and HCs.

Genome-wide analysis identifies novel shared loci between depression and white matter microstructure

Depression, a complex and heritable psychiatric disorder, is associated with alterations in white matter microstructure, yet their shared genetic basis remains largely unclear. Utilizing the largest available genome-wide association study (GWAS) datasets for depression (N = 674,452) and white matter microstructure (N = 33,224), assessed through diffusion tensor imaging metrics such as fractional anisotropy (FA) and mean diffusivity (MD), we employed linkage disequilibrium score regression method to estimate global genetic correlations, local analysis of [co]variant association approach to pinpoint genomic regions with local genetic correlations, and conjunctional false discovery rate analysis to identify shared variants. Our findings revealed that depression showed significant local genetic correlations with FA in 37 genomic regions and with MD in 59 regions, while global genetic correlations were weak. Variant-level analysis identified 78 distinct loci jointly associated with depression (25 novel loci) and FA (35 novel loci), and 41 distinct loci associated with depression (17 novel loci) and MD (25 novel loci). Further analyses showed that these shared loci exhibited both concordant and discordant effect directions between depression and white matter traits, as well as distinct yet overlapping hemispheric patterns in their genetic architecture. Enrichment analysis of these shared loci implicated biological processes related to metabolism and regulation. This study provides evidence of a mixed-direction shared genetic architecture between depression and white matter microstructure. The identification of specific loci and pathways offers potential insights for developing targeted interventions to improve white matter integrity and alleviate depressive symptoms.

Brain connectivity and transcriptomic similarity inform abnormal morphometric similarity patterns in first-episode, treatment-naïve major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is associated with disrupted brain structural integration. Morphometric similarity offers a means to capture the coordinated patterns of various structural features. However, it remains unknown whether MDD-related changes can be detected in cortical morphometric similarity through the Morphometric Inverse Divergence (MIND) network. Additionally, the role of brain connectivity in shaping these alterations, and their links to neuroreceptors and gene expression, have yet to be investigated.

METHODS

Using the T1-weighted MRI data from 71 patients with first-episode, treatment-naïve MDD and 69 healthy controls, we constructed the MIND network for all participants. We then performed between-group comparisons to investigate abnormalities in the network and spatial relationships between the observed patterns of MIND disruption and the patterns of neuroreceptors were estimated. Network-based spreading was utilized to explore the abnormalities constrained by brain connectivity based on structural, functional, and transcriptional connectome architecture and to further identify potential epicenters of MDD. In addition, partial least squares regression was conducted to examine the associations of gene expression profiles with MIND changes in MDD.

RESULTS

Patients with MDD showed significantly increased MIND in regions associated with sensation and cognition compared with healthy controls, with this altered pattern being influenced by a combination of transcriptional and structural connectivity, and potential epicenters of MDD were identified in the frontal, parietal, and paracentral cortices. Furthermore, the cortical map of case-control differences in MIND was spatially correlated with the cannabinoid CB1 receptor and the brain-wide expression of a weighted combination of genes. These genes were enriched for neurobiologically relevant pathways and preferentially expressed in different cell classes and cortical layers.

CONCLUSION

These results highlight the abnormal pattern of morphometric similarity observed in MDD, shedding light on the complex interplay between disrupted macroscale coordinated morphology and microscale molecular organization in MDD.

Structural connectivity of thalamic subnuclei in major depressive disorder: An ultra-high resolution diffusion MRI study at 7-Tesla

BACKGROUND

The thalamus serves as a central relay station within the brain, and thalamic connectional anomalies are increasingly thought to be present in major depressive disorder (MDD). However, the use of conventional MRI scanners and acquisition techniques has prevented a thorough examination of the thalamus and its subnuclear connectional profile. We combined ultra-high field diffusion MRI acquired at 7.0 Tesla to map the white matter connectivity of thalamic subnuclei.

METHODS

Fifty-three MDD patients and 12 healthy controls (HCs) were involved in the final analysis. FreeSurfer was used to segment the thalamic subnuclei, and MRtrix was used to perform the preprocessing and tractography. Fractional anisotropy, axial diffusivity, mean diffusivity, radial diffusivity, and streamline count of thalamic subnuclear tracts were measured as proxies of white matter microstructure. Bayesian multilevel model was used to assess group differences in white matter metrics for each thalamic subnuclear tract and the association between these white matter metrics and clinical features in MDD.

RESULTS

Evidence was found for reduced whiter matter metrics of the tracts spanning from all thalamic subnuclei among MDD versus HC participants. Moreover, evidence was found that white matter in various thalamic subnuclear tracts is related to medication status, age of onset and recurrence in MDD.

CONCLUSIONS

Structural connectivity was generally reduced in thalamic subnuclei in MDD participants. Several clinical characteristics are related to perturbed subnuclear thalamic connectivity with cortical and subcortical circuits that govern sensory processing, emotional function, and goal-directed behavior.

Microbiome depletion by broad-spectrum antibiotics does not influence demyelination and remyelination in cuprizone-treated mice

Demyelination in the central nervous system (CNS) is a feature of various psychiatric and neurological disorders. Emerging evidence suggests that the gut-brain axis may play a crucial role in CNS demyelination. The cuprizone (CPZ) model, which involves the administration of CPZ-containing food pellets, is commonly used to study the effects of different compounds on CNS demyelination and subsequent remyelination. This study aimed to evaluate the impact of microbiome depletion, induced by an antibiotic cocktail (ABX), on demyelination in CPZ-treated mice and the subsequent remyelination following CPZ withdrawal. Our findings indicate that a chronic 4-week oral ABX regimen, administered both during and after a 6-week CPZ exposure, does not affect demyelination or remyelination in the brains of CPZ-treated mice. Specifically, ABX treatment for 2 weeks before and 2 weeks after CPZ exposure, in the final 4 weeks before sacrifice, and for 4 weeks post-CPZ withdrawal, did not significantly alter these processes compared to control mice receiving water instead of ABX. These results indicate that despite effective microbiome depletion, a 4-week oral ABX regimen does not influence demyelination or remyelination in the CPZ model. Thus, it is unlikely that gut microbiota depletion by ABX plays a significant role in these processes. However, further research is needed to fully understand the role of the host microbiome on CPZ-induced demyelination.

Classification of Major Depressive Disorder Using Vertex-Wise Brain Sulcal Depth, Curvature, and Thickness with a Deep and a Shallow Learning Model

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing 7,012 participants from 30 sites (N=2,772 MDD and N=4,240 HC), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible. Future studies are needed to determine whether more sophisticated integration of information from other MRI modalities such as fMRI and DWI will lead to a higher performance in this diagnostic task.

Glutamate chemical exchange saturation transfer (GluCEST) MRI to evaluate the relationship between demyelination and glutamate content in depressed mice

Glutamatergic alteration is one of the potential mechanisms of depression. However, there is no consensus on whether glutamate metabolism changes affect the myelin structure of depression in mouse models. Glutamate chemical exchange saturation transfer (GluCEST) is a novel and powerful molecular imaging technique that can visualize glutamate distribution. In this study, we used the GluCEST imaging technique to look at glutamate levels in mice under chronic unpredictable mild stress (CUMS) and how they relate to demyelination. The CUMS mice were exposed to different stress factors for 6 weeks. Evaluated of depression in CUMS mice by behavioral tests. MRI scans were then performed, including T2-mapping, GluCEST, and diffusion tensor imaging (DTI) sequences. Brain tissues were collected for Luxol Fast Blue staining and immunofluorescence staining to analyze the changes in the myelin sheath. Artificially sketched regions of interest (ROI) (corpus callosum, hippocampus, and thalamus) were used to calculate the GluCEST value, fractional anisotropy (FA), and T2 value. Compared with the control group, the GluCEST value in the ROIs of CUMS mice significantly decreased. Similarly, the FA value in ROIs was lower in the CUMS group than in the CTRL group, but the T2 value did not differ significantly between the two groups. The histological results showed that ROIs in the CUMS group had demyelination compared with the CTRL group, indicating that DTI was more sensitive than T2 mapping in detecting myelin abnormalities. Furthermore, the GluCEST value in the ROIs correlates positively with the FA value. These findings suggest that altered glutamate metabolism may be one of the important factors leading to demyelination in depression, and GluCEST is expected to serve as an imaging biological marker for the diagnosis of demyelination in depression.

DeepResBat: Deep residual batch harmonization accounting for covariate distribution differences

Pooling MRI data from multiple datasets requires harmonization to reduce undesired inter-site variabilities, while preserving effects of biological variables (or covariates). The popular harmonization approach ComBat uses a mixed effect regression framework that explicitly accounts for covariate distribution differences across datasets. There is also significant interest in developing harmonization approaches based on deep neural networks (DNNs), such as conditional variational autoencoder (cVAE). However, current DNN approaches do not explicitly account for covariate distribution differences across datasets. Here, we provide mathematical results, suggesting that not accounting for covariates can lead to suboptimal harmonization. We propose two DNN-based covariate-aware harmonization approaches: covariate VAE (coVAE) and DeepResBat. The coVAE approach is a natural extension of cVAE by concatenating covariates and site information with site- and covariate-invariant latent representations. DeepResBat adopts a residual framework inspired by ComBat. DeepResBat first removes the effects of covariates with nonlinear regression trees, followed by eliminating site differences with cVAE. Finally, covariate effects are added back to the harmonized residuals. Using three datasets from three continents with a total of 2787 participants and 10,085 anatomical T1 scans, we find that DeepResBat and coVAE outperformed ComBat, CovBat and cVAE in terms of removing dataset differences, while enhancing biological effects of interest. However, coVAE hallucinates spurious associations between anatomical MRI and covariates even when no association exists. Future studies proposing DNN-based harmonization approaches should be aware of this false positive pitfall. Overall, our results suggest that DeepResBat is an effective deep learning alternative to ComBat. Code for DeepResBat can be found here: https://github.com/ThomasYeoLab/CBIG/tree/master/stable_projects/harmonization/An2024_DeepResBat.

The relationship between demographic factors and brain hierarchical changes following antidepressant treatment in patients remitted from depression

To investigate the associations between demographic factors and brain hierarchical changes following successful selective serotonin reuptake inhibitor (SSRI) treatment, 57 major depressive disorder (MDD) patients who achieved remission after a 12-week SSRI treatment and 39 healthy controls (HCs) were recruited. MDD patients underwent diffusion tensor imaging (DTI) scans before treatment and after the 12-week SSRI treatment. Depression severity was evaluated with the Hamilton Rating Scale for Depression (HAMD) using the total score and the subscales: retardation, cognitive impairment, anxiety, and sleep disturbance. All HCs also underwent DTI scans after enrollment. Building on gradient mapping techniques, we developed a set of measures to quantify the dispersion within functional communities and also studied demographic-relevant differences in the three-dimensional gradient space of remitted MDD patients. We defined the Z-scores of the gradients in the pre-treatment group relative to the HC group as the disease pattern, post-treatment group relative to the HC group as the recovery pattern. The results showed that the disease pattern of depression is associated with age, as older age groups exhibit more severe impairments in depression. A significant difference was detected in the dispersion of the frontoparietal network (FPN) between pre-treatment and post-treatment patients. With the moderating effect of the age of onset, the dispersion of the FPN was related to the improvement in cognitive impairment, the dorsal attention network (DAN) was related to the improvement in retardation symptoms. Our findings help clinicians be alert to the role of demographic effects on clinical efficacy when treating depressed patients.

Altered topology in cortical morphometric similarity network in recurrent major depressive disorder

BACKGROUND

Recurrent major depressive disorder (RDD) is increasingly understood to be associated with a 'disconnection' within the brain areas. But, the true understanding of cortical connectivities remains challenging. Morphometric similarity network (MSN) with multi-modal magnetic resonance imaging (MRI) could provide more information about cortical micro-architecture changes in individuals with RDD.

METHODS

Here, we integrated multi-modal features from T1-weighted imaging, diffusion tensor imaging (DTI), and inhomogeneous magnetization transfer imaging (ihMT) to construct MSN. We used graph theory to calculate topological changes in MSN and explore their relationship with the severity and recurrence. The topological properties of 42 RDD patients were compared with 56 age, sex, and education-matched healthy controls.

RESULTS

RDD subjects showed significantly decreased global efficiency, increased characteristic path length, reduced nodal efficiencies in the parietal lobe, subcortical area, and temporal lobe, increased betweenness centrality in the left supplementary motor area (SMA), decreased intra-modular connections in the parietal module and decreased inter-modular connections between the parietal and prefrontal modules. Notably, the global efficiency, characteristic path length, local efficiency of the right superior parietal gyrus, and inter-modular connections between the parietal and prefrontal modules were significantly associated with the number of depressive episodes. The betweenness centrality in SMA and the intra-modular connections in the parietal module showed a positive relationship with 17-item Hamilton Rating Scale for Depression (HAMD) scores.

CONCLUSIONS

The altered topology of MSN may serve as potential underlying pathological mechanisms of RDD. The impaired information integration of the network, particularly the disconnection within the fronto-parietal network, may be associated with the recurrence of depression. The SMA and the fronto-parietal network may be related to the severity of depression.

Neuroglia in mood disorders

Multiple lines of evidence indicate that mood disorders, such as major depressive and bipolar disorder, are associated with abnormalities in neuroglial cells. This chapter discusses the existing literature investigating the potential role of astrocytes, oligodendrocytes, and microglia in mood pathology. We will describe evidence from in vivo imaging, postmortem, animal models based on (stress) paradigms that mimic depressive-like behavior, and biomarker studies in blood and cerebrospinal fluid in patients with mood disorders. The effect of medication used in the treatment of mood disorders, such as antidepressants and lithium, on glial function is discussed. Lastly, we highlight the most relevant findings about potential deficiencies in glia-glia crosstalk in mood disorders. Overall, decreased astrocyte and oligodendrocyte density and expression and microglial changes in homeostatic functions have frequently been put forward in MDD pathology. Studies of BD report similar findings to some extent; however, the evidence is less well established. Together, these findings are suggestive of reduced glial cell function leading to potential white matter abnormalities, glutamate dysregulation, disrupted neuronal functioning, and neurotransmission. However, more research is required to better understand the exact mechanisms underlying glial cell contributions to mood disorder development.

Effects of arketamine on depression-like behaviors and demyelination in mice exposed to chronic restrain stress: A role of transforming growth factor-β1

BACKGROUND

Chronic restrain stress (CRS) induces depression-like behaviors and demyelination in the brain; however, the relationship between these depression-like behaviors and demyelination remains unclear. Arketamine, the (R)-enantiomer of ketamine, has shown rapid antidepressant-like effects in CRS-exposed mice.

METHODS

We examined whether arketamine can improve both depression-like behaviors and demyelination in the brains of CRS-exposed mice. Additionally, we investigated the role of transforming growth factor β1 (TGF-β1) in the beneficial effects of arketamine.

RESULTS

A single dose of arketamine (10 mg/kg) improved both depression-like behavior and demyelination in the corpus callosum of CRS-exposed mice. Correlations were found between depression-like behaviors and demyelination in this region. Furthermore, pretreatment with RepSox, an inhibitor of TGF-β1 receptor, significantly blocked the beneficial effects of arketamine on depression-like behaviors and demyelination in CRS-exposed mice. Finally, a single intranasal administration of TGF-β1 ameliorated both depression-like behaviors and demyelination in CRS-exposed mice.

LIMITATIONS

The precise mechanisms by which TGF-β1 contributes to the effects of arketamine remain unclear.

CONCLUSIONS

These data suggest that CRS-induced demyelination in the corpus callosum may contribute to depression-like behaviors, and that arketamine can mitigate these changes through a TGF-β1-dependent mechanism.

An objective quantitative diagnosis of depression using a local-to-global multimodal fusion graph neural network

This study developed an artificial intelligence (AI) system using a local-global multimodal fusion graph neural network (LGMF-GNN) to address the challenge of diagnosing major depressive disorder (MDD), a complex disease influenced by social, psychological, and biological factors. Utilizing functional MRI, structural MRI, and electronic health records, the system offers an objective diagnostic method by integrating individual brain regions and population data. Tested across cohorts from China, Japan, and Russia with 1,182 healthy controls and 1,260 MDD patients from 24 institutions, it achieved a classification accuracy of 78.75%, an area under the receiver operating characteristic curve (AUROC) of 80.64%, and correctly identified MDD subtypes. The system further discovered distinct brain connectivity patterns in MDD, including reduced functional connectivity between the left gyrus rectus and right cerebellar lobule VIIB, and increased connectivity between the left Rolandic operculum and right hippocampus. Anatomically, MDD is associated with thickness changes of the gray and white matter interface, indicating potential neuropathological conditions or brain injuries.

Macro- and Microstructural White Matter Differences in Neurologic Postacute Sequelae of SARS-CoV-2 Infection

BACKGROUND AND PURPOSE

Neuropsychiatric complications of SARS-CoV-2 infection, also known as neurologic postacute sequelae of SARS-CoV-2 infection (NeuroPASC), affect 10%-60% of infected individuals. There is growing evidence that NeuroPASC is a multi system immune dysregulation disease affecting the brain. The behavioral manifestations of NeuroPASC, such as impaired processing speed, executive function, memory retrieval, and sustained attention, suggest widespread WM involvement. Although previous work has documented WM damage following acute SARS-CoV-2 infection, its involvement in NeuroPASC is less clear. We hypothesized that macrostructural and microstructural WM differences in NeuroPASC participants would accompany cognitive and immune system differences.

MATERIALS AND METHODS

In a cross-sectional study, we screened a total of 159 potential participants and enrolled 72 participants, with 41 asymptomatic controls (NoCOVID) and 31 NeuroPASC participants matched for age, sex, and education. Exclusion criteria included neurologic disorders unrelated to SARS-CoV-2 infection. Assessments included clinical symptom questionnaires, psychometric tests, brain MRI measures, and peripheral cytokine levels. Statistical modeling included separate multivariable regression analyses of GM/WM/CSF volume, WM microstructure, cognitive, and cytokine concentration between-group differences.

RESULTS

NeuroPASC participants had larger cerebral WM volume than NoCOVID controls (β = 0.229; 95% CI: 0.017-0.441; t = 2.16; P = .035). The most pronounced effects were in the prefrontal and anterior temporal WM. NeuroPASC participants also exhibited higher WM mean kurtosis, consistent with ongoing neuroinflammation. NeuroPASC participants had more self-reported symptoms, including headache, and lower performance on measures of attention, concentration, verbal learning, and processing speed. A multivariate profile analysis of the cytokine panel showed different group cytokine profiles (Wald-type-statistic = 44.6, P = .046), with interferon (IFN)-λ1 and IFN-λ2/3 levels higher in the NeuroPASC group.

CONCLUSIONS

NeuroPASC participants reported symptoms of lower concentration, higher fatigue, and impaired cognition compatible with WM syndrome. Psychometric testing confirmed these findings. NeuroPASC participants exhibited larger cerebral WM volume and higher WM mean kurtosis than NoCOVID controls. These findings suggest that immune dysregulation could influence WM properties to produce WM volume increases and consequent cognitive effects and headaches. Further work will be needed to establish mechanistic links among these variables.

A Reproducible Pipeline for Parcellation of the Anterior Limb of the Internal Capsule

BACKGROUND

The anterior limb of the internal capsule (ALIC) is a white matter structure that connects the prefrontal cortex (PFC) to the brainstem, thalamus, and subthalamic nucleus. It is a target for deep brain stimulation for obsessive-compulsive disorder. There is strong interest in improving deep brain stimulation targeting by using diffusion tractography to reconstruct and target specific ALIC fiber pathways, but this methodology is susceptible to errors and lacks validation. To address these limitations, we developed a novel diffusion tractography pipeline that generates reliable and biologically validated ALIC white matter reconstructions.

METHODS

Following algorithm development and refinement, we analyzed 43 control participants, each with 2 sets of 3T magnetic resonance imaging data and a subset of 5 control participants with 7T data from the Human Connectome Project. We generated 22 segmented ALIC fiber bundles (11 per hemisphere) based on PFC regions of interest, and we analyzed the relationships among bundles.

RESULTS

We successfully reproduced the topographies established by previous anatomical work using images acquired at both 3T and 7T. Quantitative assessment demonstrated significantly smaller intraparticipant variability than interparticipant variability for both test and retest groups across all but one PFC region. We examined the overlap between fibers from different PFC regions and a response tract for obsessive-compulsive disorder deep brain stimulation, and we reconstructed the PFC hyperdirect pathway using a modified version of our pipeline.

CONCLUSIONS

Our diffusion magnetic resonance imaging algorithm reliably generates biologically validated ALIC white matter reconstructions, thereby allowing for more precise modeling of fibers for neuromodulation therapies.

Structural-functional connectomics in major depressive disorder following aiTBS treatment

Major depressive disorder (MDD) has been associated with changes in the structural (SC) and functional connectivity (FC) of the brain. This study investigated the effects of accelerated intermittent theta burst stimulation (aiTBS) on SC-FC coupling and graph theory measures, focusing on the association between baseline SC-FC coupling of the dorsolateral prefrontal cortex (dlPFC) and clinical improvement. In a randomized, sham-controlled, quadruple-blind, crossover study, aiTBS was delivered to the left dlPFC of depressed patients with MDD, and diffusion tensor imaging (DTI) and resting-state functional magnetic resonance imaging (rsfMRI) data were acquired. In 77 MDD patients, significantly increased whole-brain SC-FC coupling was observed, primarily driven by default mode network (DMN) SC-FC coupling, along with increased somatomotor network FC, and decreased FC between the DMN hubs and limbic regions after active aiTBS. Furthermore, significant increases were observed in structural global and local efficiency measures that were not specific to the stimulation condition (active/sham aiTBS). However, these changes did not significantly correlate with clinical improvement. Notably, baseline SC-FC coupling of the left dlPFC was a significant predictor of clinical improvement. Our findings highlight the potential of left dlPFC SC-FC coupling as a predictor of aiTBS treatment outcomes, as well as the effect of aiTBS in enhancing SC-FC coupling.

Exploring the Complex Relationship Between Antidepressants, Depression and Neurocognitive Disorders

The coexistence of dementia and depression in older populations presents a complex clinical challenge, with each condition often exacerbating the other. Cognitive decline can intensify mood disturbances, and untreated or recurring depression accelerates neurodegenerative processes. As depression is a recognized risk factor for dementia, it is crucial to address both conditions concurrently to prevent further deterioration. Antidepressants are frequently used to manage depression in dementia patients, with some studies suggesting they offer neuroprotective benefits. These benefits include promoting neurogenesis, enhancing synaptic plasticity, and reducing neuroinflammation, potentially slowing cognitive decline. Additionally, antidepressants have shown promise in addressing Alzheimer's-related pathologies by reducing amyloid-beta accumulation and tau hyperphosphorylation. However, treatment-resistant depression remains a significant challenge, particularly in older adults with cognitive impairment. Many do not respond well to standard antidepressant therapies due to advanced neurodegenerative changes. Conflicting findings from studies add to the uncertainty, with some research suggesting that antidepressants may increase dementia risk, especially when used in patients with undiagnosed early-stage dementia. This article aims to explore the intricate relationship between depression and dementia, examining the benefits and risks of antidepressant use. We highlight the urgent need for personalized, comprehensive treatment strategies that balance mental health improvement with cognitive protection.

White matter organization abnormalities in adults with 47,XXX: A 7 Tesla MRI study

47,XXX (Triple X syndrome) is a sex chromosome aneuploidy characterized by the presence of a supernumerary X chromosome in affected females, and has been associated with a variable cognitive, behavioral, and psychiatric phenotype. Alterations in brain gray matter structure and function have been reported, but less is known about white matter (WM) organization in 47,XXX. Therefore, we conducted 7 T diffusion tensor imaging and characterized fractional anisotropy, mean diffusivity, axial diffusivity, and radial diffusivity of 22 adult women with 47,XXX and 22 age-matched typically developing females using tract-based spatial statistics. Relationships between phenotypic traits and WM organization characteristics in 47,XXX were also investigated. Adults with 47,XXX showed lower axial diffusivity in the body of the corpus callosum and the right superior longitudinal fasciculus. WM organization variability was not associated with IQ and social cognition and social functioning deficits in 47,XXX. Our findings indicate an effect of a supernumerary X chromosome in adult women on axonal integrity of the body of the corpus callosum and the right superior longitudinal fasciculus. These findings provide additional insight into the role of the X chromosome on WM organization. Future research is warranted to explore the clinical significant impact of altered WM organization in 47,XXX.

Transdiagnostic alterations in white matter microstructure associated with suicidal thoughts and behaviours in the ENIGMA Suicidal Thoughts and Behaviours consortium

Previous studies have suggested that alterations in white matter (WM) microstructure are implicated in suicidal thoughts and behaviours (STBs). However, findings of diffusion tensor imaging (DTI) studies have been inconsistent. In this large-scale mega-analysis conducted by the ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium, we examined WM alterations associated with STBs. Data processing was standardised across sites, and resulting WM microstructure measures (fractional anisotropy, axial diffusivity, mean diffusivity and radial diffusivity) for 25 WM tracts were pooled across 40 cohorts. We compared these measures among individuals with a psychiatric diagnosis and lifetime history of suicide attempt (n=652; mean age=35.4±14.7; female=71.8%), individuals with a psychiatric diagnosis but no STB (i.e., clinical controls; n=1871; mean age=34±14.8; female=59.8%), and individuals with no mental disorder diagnosis and no STB (i.e., healthy controls; n=642; mean age=29.6±13.1; female=62.9%). We also compared these measures among individuals with recent suicidal ideation (n=714; mean age=36.3±15.3; female=66.1%), clinical controls (n=1184; mean age=36.8±15.6; female=63.1%), and healthy controls (n=1240; mean age= 31.6±15.5; female=61.0%). We found subtle but statistically significant effects, such as lower fractional anisotropy associated with a history of suicide attempt, over and above the effect of psychiatric diagnoses. These effects were strongest in the corona radiata, thalamic radiation, fornix/stria terminalis, corpus callosum and superior longitudinal fasciculus. Effect sizes were small (Cohen's d < 0.25). Recent suicidal ideation was not associated with alterations in WM microstructure. This large-scale coordinated mega-analysis revealed subtle regional and global alterations in WM microstructure in individuals with a history of suicide attempt. Longitudinal studies are needed to confirm whether these alterations are a risk factor for suicidal behaviour.

Brain-based correlates of depression and traumatic brain injury: a systematic review of structural and functional magnetic resonance imaging studies

Introduction

Depression is prevalent after traumatic brain injury (TBI). However, there is a lack of understanding of the brain-based correlates of depression post-TBI. This systematic review aimed to synthesize findings of structural and functional magnetic resonance imaging (MRI) studies to identify consistently reported neural correlates of depression post-TBI.

Methods

A search for relevant published studies was conducted through OVID (MEDLINE, APA PsycINFO, and Embase), with an end date of August 3rd, 2023. Fourteen published studies were included in this review.

Results

TBI patients with depression exhibited distinct changes in diffusion- based white matter fractional anisotropy, with the direction of change depending on the acuteness or chronicity of TBI. Decreased functional connectivity (FC) of the salience and default mode networks was prominent alongside the decreased volume of gray matter within the insular, dorsomedial prefrontal, and ventromedial prefrontal cortices. Seven studies reported the correlation between observed neuroimaging and depression outcomes. Of these studies, 42% indicated that FC of the bilateral medial temporal lobe subregions was correlated with depression outcomes in TBI.

Discussion

This systematic review summarizes existing neuroimaging evidence and reports brain regions that can be leveraged as potential treatment targets in future studies examining depression post-TBI.

Contrasting association pattern of plasma low-density lipoprotein with white matter integrity in APOE4 carriers versus non-carriers

Apolipoprotein E ε4 (APOE4) is a strong genetic risk factor of Alzheimer's disease and metabolic dysfunction. However, whether APOE4 and markers of metabolic dysfunction synergistically impact the deterioration of white matter (WM) integrity in older adults remains unknown. In the UK Biobank data, we conducted a multivariate analysis to investigate the interactions between APOE4 and 249 plasma metabolites (measured using nuclear magnetic resonance spectroscopy) with whole-brain WM integrity (measured by diffusion-weighted magnetic resonance imaging) in a cohort of 1917 older adults (aged 65.0-81.0 years; 52.4 % female). Although no main association was observed between either APOE4 or metabolites with WM integrity (adjusted P > 0.05), significant interactions between APOE4 and metabolites with WM integrity were identified. Among the examined metabolites, higher concentrations of low-density lipoprotein and very low-density lipoprotein were associated with a lower level of WM integrity (b=-0.12, CI=-0.14,-0.10) among APOE4 carriers. Conversely, among non-carriers, they were associated with a higher level of WM integrity (b=0.05, CI=0.04,0.07), demonstrating a significant moderation role of APOE4 (b =-0.18, CI=-0.20,-0.15, P<0.00001).

Structural MRI findings in the brain related to pain distribution in chronic overlapping pain conditions: An explorative case-control study in females with fibromyalgia, temporomandibular disorder-related chronic pain and pain-free controls

BACKGROUND

Few neuroimaging studies have investigated structural brain differences associated with variations in pain distribution.

OBJECTIVE

To explore structural differences of the brain in fibromyalgia (FM), temporomandibular disorder pain (TMD) and healthy pain-free controls (CON) using structural and diffusion MRI.

METHODS

A case-control exploratory study with three study groups with different pain distribution were recruited: FM (n = 16; mean age [standard deviation]: 44 [14] years), TMD (n = 17, 39 [14] years) and CON (n = 10, 37 [14] years). Participants were recruited at the University Dental Clinic in Malmö, Sweden. T1-weighted and diffusion MRIs were acquired, clinical and psychosocial measures were obtained. Main outcome measures were subcortical volume, cortical thickness, white matter microstructure and whole brain grey matter intensity.

RESULTS

Patients with FM had smaller volume in the right thalamus than patients with TMD (p = .020) and CON (p = .030). The right thalamus volume was negatively correlated to pain intensity (r = -0.37, p = .022) and pain-related disability (r = -0.45, p = .004). The FM group had lower cortical thickness in the right anterior prefrontal cortex than CON (p = .005). Cortical thickness in this area was negatively correlated to pain intensity (r [37] = - 0.48, p = .002).

CONCLUSIONS

This study suggests that thalamus grey matter alterations are associated with FM and TMD, and that anterior prefrontal cortex grey matter alterations are associated with FM but not TMD. Studies on chronic overlapping pain conditions are needed in relation to possible nociplastic pain mechanisms in the brain and central nervous system.

A review of diffusion MRI in mood disorders: mechanisms and predictors of treatment response

By measuring the molecular diffusion of water molecules in brain tissue, diffusion MRI (dMRI) provides unique insight into the microstructure and structural connections of the brain in living subjects. Since its inception, the application of dMRI in clinical research has expanded our understanding of the possible biological bases of psychiatric disorders and successful responses to different therapeutic interventions. Here, we review the past decade of diffusion imaging-based investigations with a specific focus on studies examining the mechanisms and predictors of therapeutic response in people with mood disorders. We present a brief overview of the general application of dMRI and key methodological developments in the field that afford increasingly detailed information concerning the macro- and micro-structural properties and connectivity patterns of white matter (WM) pathways and their perturbation over time in patients followed prospectively while undergoing treatment. This is followed by a more in-depth summary of particular studies using dMRI approaches to examine mechanisms and predictors of clinical outcomes in patients with unipolar or bipolar depression receiving pharmacological, neurostimulation, or behavioral treatments. Limitations associated with dMRI research in general and with treatment studies in mood disorders specifically are discussed, as are directions for future research. Despite limitations and the associated discrepancies in findings across individual studies, evolving research strongly indicates that the field is on the precipice of identifying and validating dMRI biomarkers that could lead to more successful personalized treatment approaches and could serve as targets for evaluating the neural effects of novel treatments.

Associations between white matter microstructure and cognitive decline in major depressive disorder versus controls in Germany: a prospective case-control cohort study

BACKGROUND

Cognitive deficits are a key source of disability in individuals with major depressive disorder (MDD) and worsen with disease progression. Despite their clinical relevance, the underlying mechanisms of cognitive deficits remain poorly elucidated, hampering effective treatment strategies. Emerging evidence suggests that alterations in white matter microstructure might contribute to cognitive dysfunction in MDD. We aimed to investigate the complex association between changes in white matter integrity, cognitive decline, and disease course in MDD in a comprehensive longitudinal dataset.

METHODS

In the naturalistic, observational, prospective, case-control Marburg-Münster Affective Disorders Cohort Study, individuals aged 18-65 years and of Caucasian ancestry were recruited from local psychiatric hospitals in Münster and Marburg, Germany, and newspaper advertisements. Individuals diagnosed with MDD and individuals without any history of psychiatric disorder (ie, healthy controls) were included in this subsample analysis. Participants had diffusion-weighted imaging, a battery of neuropsychological tests, and detailed clinical data collected at baseline and at 2 years of follow-up. We used linear mixed-effect models to compare changes in cognitive performance and white matter integrity between participants with MDD and healthy controls. Diffusion-weighted imaging analyses were conducted using tract-based spatial statistics. To correct for multiple comparisons, threshold free cluster enhancement (TFCE) was used to correct α-values at the family-wise error rate (FWE; ptfce-FWE). Effect sizes were estimated by conditional, partial R2 values (sr2) following the Nakagawa and Schielzeth method to quantify explained variance. The association between changes in cognitive performance and changes in white matter integrity was analysed. Finally, we examined whether the depressive disease course between assessments predicted cognitive performance at follow-up and whether white matter integrity mediated this association. People with lived experience were not involved in the research and writing process.

FINDINGS

881 participants were selected for our study, of whom 418 (47%) had MDD (mean age 36·8 years [SD 13·4], 274 [66%] were female, and 144 [34%] were male) and 463 (53%) were healthy controls (mean age 35·6 years [13·5], 295 [64%] were female, and 168 [36%] were male). Baseline assessments were done between Sept 11, 2014, and June 3, 2019, and after a mean follow-up of 2·20 years (SD 0·19), follow-up assessments were done between Oct 6, 2016, and May 31, 2021. Participants with MDD had lower cognitive performance than did healthy controls (p<0·0001, sr2=0·056), regardless of timepoint. Analyses of diffusion-weighted imaging indicated a significant diagnosis × time interaction with a steeper decline in white matter integrity of the superior longitudinal fasciculus over time in participants with MDD than in healthy controls (ptfce-FWE=0·026, sr2=0·002). Furthermore, cognitive decline was robustly associated with the decline in white matter integrity over time across both groups (ptfce-FWE<0·0001, sr2=0·004). In participants with MDD, changes in white matter integrity (p=0·0040, β=0·071) and adverse depressive disease course (p=0·0022, β=-0·073) independently predicted lower cognitive performance at follow-up.

INTERPRETATION

Alterations of white matter integrity occurred over time to a greater extent in participants with MDD than in healthy controls, and decline in white matter integrity was associated with a decline in cognitive performance across groups. Our findings emphasise the crucial role of white matter microstructure and disease progression in depression-related cognitive dysfunction, making both priority targets for future treatment development.

FUNDING

German Research Foundation (DFG).

Intrinsic disruption of white matter microarchitecture in major depressive disorder: A voxel-based meta analysis of diffusion tensor imaging

BACKGROUND

Major depressive disorder (MDD) is a prevalent and disabling mood disorder, thought to be linked with brain white matter (WM) alterations. Prior diffusion tensor imaging (DTI) studies have reported inconsistent changes in fractional anisotropy (FA) across different brain regions in MDD patients. However, none of these studies utilized raw t-map data for WM meta-analysis in MDD. Our study aims to address this gap by conducting a whole-brain-based meta-analysis of FA in MDD using Seed-based d mapping via permutation of subject images (SDM-PSI), combining reported peak coordinates and raw statistical parametric maps.

OBJECTIVES

Following PRISMA guidelines, we performed a systematic search and meta-analysis to compare FA in MDD patients with healthy controls (HC). Our goal was to identify WM abnormalities in MDD, using SDM, which could shed light on the disorder's pathogenesis.

RESULTS

The meta-analysis included 39 studies with 3696 participants (2094 with MDD, 1602HC). It revealed that MDD patients, in comparison to HC, have lower FA in the corpus callosum (CC) and anterior thalamic projections (ATP). Subgroup analyses indicated that the CC is a more stable pathogenic factor in MDD. Meta-regression analyses showed no linear correlation between the mean age, percentage of female patients, duration of depression, and FA abnormalities. This suggests that WM impairments in interhemispheric connections and anterior thalamocortical circuits are significant in the pathogenesis of MDD.

Altered sleep onset transition in depression: Evidence from EEG activity and EEG functional connectivity analyses

OBJECTIVE

Sleep disorders constitute a principal diagnostic criterion for depression, potentially reflecting the abnormal persistence of brain activity during the sleep onset (SO) transition. Here, we sought to explore the differences in the dynamic changes in the EEG activity and the EEG functional connectivity (FC) during the SO transition in depressed patients.

METHODS

Overnight polysomnography recordings were obtained from thirty-two depressed patients and thirty-three healthy controls. The multiscale permutation entropy (MSPE) and EEG relative power were extracted to characterize EEG activity, and weighted phase lag index (WPLI) was calculated to characterize EEG FC.

RESULTS

The intergroup differences in EEG activity of relative power and MSPE were reversed near SO, which attributed to slower rates of change among depressed patients. Regarding the characteristics of the EEG FC network, depressed patients exhibited significantly higher inter-hemispheric and interregional WPLI values in both delta and alpha bands throughout the SO transition, concomitant with different dynamic properties in the delta band FC. During the process after SO, patients exhibited increased inter-hemispheric long-range links, whereas controls showed more intra-hemispheric ones. Finally, we found significant correlations in the dynamic changes between different EEG measures.

CONCLUSIONS

Our research revealed that the abnormal changes during the SO transition in depressed patients were manifested in both homeostatic and dynamic aspects, which were reflected in EEG FC and EEG activity, respectively.

SIGNIFICANCE

These findings may elucidate the mechanism underlying sleep disorders in depression from the perspective of neural activity.

The interplay between polygenic score for tumor necrosis factor-α, brain structural connectivity, and processing speed in major depression

Reduced processing speed is a core deficit in major depressive disorder (MDD) and has been linked to altered structural brain network connectivity. Ample evidence highlights the involvement of genetic-immunological processes in MDD and specific depressive symptoms. Here, we extended these findings by examining associations between polygenic scores for tumor necrosis factor-α blood levels (TNF-α PGS), structural brain connectivity, and processing speed in a large sample of MDD patients. Processing speed performance of n = 284 acutely depressed, n = 177 partially and n = 198 fully remitted patients, and n = 743 healthy controls (HC) was estimated based on five neuropsychological tests. Network-based statistic was used to identify a brain network associated with processing speed. We employed general linear models to examine the association between TNF-α PGS and processing speed. We investigated whether network connectivity mediates the association between TNF-α PGS and processing speed. We identified a structural network positively associated with processing speed in the whole sample. We observed a significant negative association between TNF-α PGS and processing speed in acutely depressed patients, whereas no association was found in remitted patients and HC. The mediation analysis revealed that brain connectivity partially mediated the association between TNF-α PGS and processing speed in acute MDD. The present study provides evidence that TNF-α PGS is associated with decreased processing speed exclusively in patients with acute depression. This association was partially mediated by structural brain connectivity. Using multimodal data, the current findings advance our understanding of cognitive dysfunction in MDD and highlight the involvement of genetic-immunological processes in its pathomechanisms.

Nongenetic and Genetic Factors Associated with White Matter Brain Aging: Exposome-Wide and Genome-Wide Association Study

BACKGROUND/OBJECTIVES

Human brain aging is a complex process that affects various aspects of brain function and structure, increasing susceptibility to neurological and psychiatric disorders. A number of nongenetic (e.g., environmental and lifestyle) and genetic risk factors are found to contribute to the varying rates at which the brain ages among individuals.

METHODS

In this paper, we conducted both an exposome-wide association study (XWAS) and a genome-wide association study (GWAS) on white matter brain aging in the UK Biobank, revealing the multifactorial nature of brain aging. We applied a machine learning algorithm and leveraged fractional anisotropy tract measurements from diffusion tensor imaging data to predict the white matter brain age gap (BAG) and treated it as the marker of brain aging. For XWAS, we included 107 variables encompassing five major categories of modifiable exposures that potentially impact brain aging and performed both univariate and multivariate analysis to select the final set of nongenetic risk factors.

RESULTS

We found current tobacco smoking, dietary habits including oily fish, beef, lamb, cereal, and coffee intake, length of mobile phone use, use of UV protection, and frequency of solarium/sunlamp use were associated with the BAG. In genetic analysis, we identified several SNPs on chromosome 3 mapped to genes IP6K1, GMNC, OSTN, and SLC25A20 significantly associated with the BAG, showing the high heritability and polygenic architecture of human brain aging.

CONCLUSIONS

The critical nongenetic and genetic risk factors identified in our study provide insights into the causal relationship between white matter brain aging and neurodegenerative diseases.

Longitudinal development of resting-state functional connectivity in adolescents with and without internalizing disorders

Longitudinal studies using resting-state functional magnetic resonance imaging (rs-fMRI) focused on adolescent internalizing psychopathology are scarce and have mostly investigated standardized treatment effects on functional connectivity (FC) of the full amygdala. The role of amygdala subregions and large resting-state networks had yet to be elucidated, and treatment is in practice often personalized. Here, longitudinal FC development of amygdala subregions and whole-brain networks are investigated in a clinically representative sample. Treatment-naïve adolescents with clinical depression and comorbid anxiety who started care-as-usual (n = 23; INT) and healthy controls (n = 24; HC) participated in rs-fMRI scans and questionnaires at baseline (before treatment) and after three months. Changes between and within groups over time in FC of the laterobasal amygdala (LBA), centromedial amygdala (CMA) and whole-brain networks derived from independent component analysis (ICA) were investigated. Groups differed significantly in FC development of the right LBA to the postcentral gyrus and the left LBA to the frontal pole. Within INT, FC to the frontal pole and postcentral gyrus changed over time while changes in FC of the right LBA were also linked to symptom change. No significant interactions were observed when considering FC from CMA bilateral seeds or within ICA-derived networks. Results in this cohort suggest divergent longitudinal development of FC from bilateral LBA subregions in adolescents with internalizing disorders compared to healthy peers, possibly reflecting nonspecific treatment effects. Moreover, associations were found with symptom change. These results highlight the importance of differentiation of amygdala subregions in neuroimaging research in adolescents.

Shared and Distinct White Matter Alterations in Major Depression and Bipolar Disorder: A Systematic Review and Meta-Analysis

BACKGROUND

Identifying white matter (WM) microstructural similarities and differences between major depressive disorder (MDD) and bipolar disorder (BD) is an important way to understand the potential neuropathological mechanism in emotional disorders. Numerous diffusion tensor imaging (DTI) studies over recent decades have confirmed the presence of WM anomalies in these two affective disorders, but the results were inconsistent. This study aimed to determine the statistical consistency of DTI findings for BD and MDD by using the coordinate-based meta-analysis (CBMA) approach.

METHODS

We performed a systematic search of tract-based spatial statistics (TBSS) studies comparing MDD or BD with healthy controls (HC) as of June 30, 2024. The seed-based d-mapping (SDM) was applied to investigate fractional anisotropy (FA) changes. Meta-regression was then used to analyze the potential correlations between demographics and neuroimaging alterations.

RESULTS

Regional FA reductions in the body of the corpus callosum (CC) were identified in both of these two diseases. Besides, MDD patients also exhibited decreased FA in the genu and splenium of the CC, as well as the left anterior thalamic projections (ATP), while BD patients showed FA reduction in the left median network, and cingulum in addition to the CC.

CONCLUSIONS

The results highlighted that altered integrity in the body of CC served as the shared basis of MDD and BD, and distinct microstructural WM abnormalities also existed, which might induce the various clinical manifestations of these two affective disorders. The study was registered on PROSPERO (http://www.crd.york.ac.uk/PROSPERO), registration number: CRD42022301929.

Posttraumatic survivor guilt is associated with white matter microstructure alterations

BACKGROUND

Military veterans with posttraumatic stress disorder (PTSD) commonly experience posttraumatic guilt. Guilt over commission or omission evolves when responsibility is assumed for an unfortunate outcome (e.g., the death of a fellow combatant). Survivor guilt is a state of intense emotional distress experienced by the weight of knowing that one survived while others did not.

METHODS

This study of the Translational Research Center for TBI and Stress Disorders (TRACTS) analyzed structural and diffusion-weighted magnetic resonance imaging data from 132 male Iraq/Afghanistan veterans with PTSD. The Clinician-Administered PTSD Scale for DSM-IV (CAPS-IV) was employed to classify guilt. Thirty (22.7 %) veterans experienced guilt over acts of commission or omission, 34 (25.8 %) experienced survivor guilt, and 68 (51.5 %) had no posttraumatic guilt. White matter microstructure (fractional anisotropy, FA), cortical thickness, and cortical volume were compared between veterans with guilt over acts of commission or omission, veterans with survivor guilt, and veterans without guilt.

RESULTS

Veterans with survivor guilt had significantly lower white matter FA compared to veterans who did not experience guilt (p < .001), affecting several regions of major white matter fiber bundles. There were no significant differences in white matter FA, cortical thickness, or volumes between veterans with guilt over acts of commission or omission and veterans without guilt (p > .050).

LIMITATIONS

This cross-sectional study with exclusively male veterans precludes inferences of causality between the studied variables and generalizability to the larger veteran population that includes women.

CONCLUSION

Survivor guilt may be a particularly impactful form of posttraumatic guilt that requires specific treatment efforts targeting brain health.

A worldwide study of white matter microstructural alterations in people living with Parkinson's disease

The progression of Parkinson's disease (PD) is associated with microstructural alterations in neural pathways, contributing to both motor and cognitive decline. However, conflicting findings have emerged due to the use of heterogeneous methods in small studies. Here we performed a large diffusion MRI study in PD, integrating data from 17 cohorts worldwide, to identify stage-specific profiles of white matter differences. Diffusion-weighted MRI data from 1654 participants diagnosed with PD (age: 20-89 years; 33% female) and 885 controls (age: 19-84 years; 47% female) were analyzed using the ENIGMA-DTI protocol to evaluate white matter microstructure. Skeletonized maps of fractional anisotropy (FA) and mean diffusivity (MD) were compared across Hoehn and Yahr (HY) disease groups and controls to reveal the profile of white matter alterations at different stages. We found an enhanced, more widespread pattern of microstructural alterations with each stage of PD, with eventually lower FA and higher MD in almost all regions of interest: Cohen's d effect sizes reached d = -1.01 for FA differences in the fornix at PD HY Stage 4/5. The early PD signature in HY stage 1 included higher FA and lower MD across the entire white matter skeleton, in a direction opposite to that typical of other neurodegenerative diseases. FA and MD were associated with motor and non-motor clinical dysfunction. While overridden by degenerative changes in the later stages of PD, early PD is associated with paradoxically higher FA and lower MD in PD, consistent with early compensatory changes associated with the disorder.

Demyelination in Patients with POST-COVID Depression

Background: Depression is one of the most severe sequelae of COVID-19, with major depressive disorder often characterized by disruption in white matter (WM) connectivity stemming from changes in brain myelination. This study aimed to quantitatively assess brain myelination in clinically diagnosed post-COVID depression (PCD) using the recently proposed MRI method, macromolecular proton fraction (MPF) mapping. Methods: The study involved 63 recovered COVID-19 patients (52 mild, 11 moderate, and 2 severe) at 13.5 ± 10.0 months post-recovery, with matched controls without prior COVID-19 history (n = 19). A post-COVID depression group (PCD, n = 25) was identified based on psychiatric diagnosis, while a comparison group (noPCD, n = 38) included participants with neurological COVID-19 complications, excluding clinical depression. Results: Fast MPF mapping revealed extensive demyelination in PCD patients, particularly in juxtacortical WM (predominantly occipital lobe and medial surface), WM tracts (inferior fronto-occipital fasciculus (IFOF), posterior thalamic radiation, external capsule, sagittal stratum, tapetum), and grey matter (GM) structures (hippocampus, putamen, globus pallidus, and amygdala). The noPCD group also displayed notable demyelination, but with less magnitude and propagation. Multiple regression analysis highlighted IFOF demyelination as the primary predictor of Hamilton scores, PCD presence, and severity. The number of post-COVID symptoms was a significant predictor of PCD presence, while the number of acute symptoms was a significant predictor of PCD severity. Conclusions: This study, for the first time, reveals extensive demyelination in numerous WM and GM structures in PCD, outlining IFOF demyelination as a key biomarker.

Microstructural brain assessment in late-life depression and apathy using diffusion MRI multi-compartments models and tractometry

Late-life depression (LLD) is both common and disabling and doubles the risk of dementia onset. Apathy might constitute an additional risk of cognitive decline but clear understanding of its pathophysiology is lacking. While white matter (WM) alterations have been assessed using diffusion tensor imaging (DTI), this model cannot accurately represent WM microstructure. We hypothesized that a more complex multi-compartment model would provide new biomarkers of LLD and apathy. Fifty-six individuals (LLD n = 35, 26 females, 75.2 ± 6.4 years, apathy evaluation scale scores (41.8 ± 8.7) and Healthy controls, n = 21, 16 females, 74.7 ± 5.2 years) were included. In this article, a tract-based approach was conducted to investigate novel diffusion model biomarkers of LLD and apathy by interpolating microstructural metrics directly along the fiber bundle. We performed multivariate statistical analysis, combined with principal component analysis for dimensional data reduction. We then tested the utility of our framework by demonstrating classically reported from the literature modifications in LDD while reporting new results of biological-basis of apathy in LLD. Finally, we aimed to investigate the relationship between apathy and microstructure in different fiber bundles. Our study suggests that new fiber bundles, such as the striato-premotor tracts, may be involved in LLD and apathy, which bring new light of apathy mechanisms in major depression. We also identified statistical changes in diffusion MRI metrics in 5 different tracts, previously reported in major cognitive disorders dementia, suggesting that these alterations among these tracts are both involved in motivation and cognition and might explain how apathy is a prodromal phase of degenerative disorders.

Multimodal brain-derived subtypes of Major depressive disorder differentiate patients for anergic symptoms, immune-inflammatory markers, history of childhood trauma and treatment-resistance

An estimated 30 % of Major Depressive Disorder (MDD) patients exhibit resistance to conventional antidepressant treatments. Identifying reliable biomarkers of treatment-resistant depression (TRD) represents a major goal of precision psychiatry, which is hampered by the clinical and biological heterogeneity. To uncover biologically-driven subtypes of MDD, we applied an unsupervised data-driven framework to stratify 102 MDD patients on their neuroimaging signature, including extracted measures of cortical thickness, grey matter volumes, and white matter fractional anisotropy. Our novel analytical pipeline integrated different machine learning algorithms to harmonize data, perform data dimensionality reduction, and provide a stability-based relative clustering validation. The obtained clusters were characterized for immune-inflammatory peripheral biomarkers, TRD, history of childhood trauma and depressive symptoms. Our results indicated two different clusters of patients, differentiable with 67 % of accuracy: one cluster (n = 59) was associated with a higher proportion of TRD, and higher scores of energy-related depressive symptoms, history of childhood abuse and emotional neglect; this cluster showed a widespread reduction in cortical thickness (d = 0.43-1.80) and volumes (d = 0.45-1.05), along with fractional anisotropy in the fronto-occipital fasciculus, stria terminalis, and corpus callosum (d = 0.46-0.52); the second cluster (n = 43) was associated with cognitive and affective depressive symptoms, thicker cortices and wider volumes. Multivariate analyses revealed distinct brain-inflammation relationships between the two clusters, with increase in pro-inflammatory markers being associated with decreased cortical thickness and volumes. Our stratification of MDD patients based on structural neuroimaging identified clinically-relevant subgroups of MDD with specific symptomatic and immune-inflammatory profiles, which can contribute to the development of tailored personalized interventions for MDD.

Linked patterns of symptoms and cognitive covariation with functional brain controllability in major depressive disorder

BACKGROUND

Controllability analysis is an approach developed for evaluating the ability of a brain region to modulate function in other regions, which has been found to be altered in major depressive disorder (MDD). Both depressive symptoms and cognitive impairments are prominent features of MDD, but the case-control differences of controllability between MDD and controls can not fully interpret the contribution of both clinical symptoms and cognition to brain controllability and linked patterns among them in MDD.

METHODS

Sparse canonical correlation analysis was used to investigate the associations between resting-state functional brain controllability at the network level and clinical symptoms and cognition in 99 first-episode medication-naïve patients with MDD.

FINDINGS

Average controllability was significantly correlated with clinical features. The average controllability of the dorsal attention network (DAN) and visual network had the highest correlations with clinical variables. Among clinical variables, depressed mood, suicidal ideation and behaviour, impaired work and activities, and gastrointestinal symptoms were significantly negatively associated with average controllability, and reduced cognitive flexibility was associated with reduced average controllability.

INTERPRETATION

These findings highlight the importance of brain regions in modulating activity across brain networks in MDD, given their associations with symptoms and cognitive impairments observed in our study. Disrupted control of brain reconfiguration of DAN and visual network during their state transitions may represent a core brain mechanism for the behavioural impairments observed in MDD.

FUNDING

National Natural Science Foundation of China (82001795 and 82027808), National Key R&D Program (2022YFC2009900), and Sichuan Science and Technology Program (2024NSFSC0653).

Examining the connection between weekend catch-up sleep and depression: Insights from 2017 to 2020 NHANES information

BACKGROUND

Depression, a prevalent mental disorder, has shown an increasing trend in recent years, imposing a significant burden on health and society. Adequate sleep has been proven to reduce the incidence of depression. This study seeks to explore how Weekend Catch-up Sleep (WCS) is connected with the prevalence of depression in the American population.

METHODS

The National Health and Nutrition Examination Survey (NHANES) provides representative data for the U.S.

POPULATION

We utilized data from the 2017-2018 and 2019-2020 cycles. Depression was operationally defined as a PHQ-9 score exceeding 10. WCS duration was categorized into five groups: no change in sleep duration (=0 h), decreased sleep duration (<0), short catch-up sleep duration (>0 h, ≤1 h), moderate catch-up sleep duration (>1 h, <2 h), and long catch-up sleep duration (≥2 h).

RESULTS

Among the 8039 individuals, the distribution of WCS duration was as follows: no change (WCS = 0 h) in 2999 individuals (37.3 %), decreased sleep (WCS < 0 h) in 1199 individuals (14.9 %), short catch-up sleep (0 h < WCS ≤ 1 h) in 1602 individuals (19.9 %), moderate catch-up sleep (1 h < WCS < 2 h) in 479 individuals (6.0 %), and long catch-up sleep (WCS ≥ 2 h) in 1760 individuals (21.9 %). Acting by adjustment for all covariates in a multiple regression analysis, we discovered that persons with 1 to 2 h of weekend catch-up sleep had a substantially low prevalence of depression concerning those with WCS = 0 (OR 0.22, 95 % CI 0.08-0.59, P = 0.007).

CONCLUSION

The prevalence of depression in individuals engaging in weekend catch-up sleep for 1 to 2 h is lower than those who do not catch up on weekends. This discovery on the treatment and prevention of depression provides a new perspective. However, further prospective research and clinical trials are needed for a comprehensive investigation.

Plasma Apo-E mediated corticospinal tract abnormalities and suicidality in patients with major depressive disorder

This study aims to explore the link between Apo-E, brain white matter, and suicide in patients with major depressive disorder (MDD) to investigate the potential neuroimmune mechanisms of Apo-E that may lead to suicide. Thirty-nine patients with MDD (22 patients with suicidality) and 57 age, gender, and education-matched healthy controls participated in this study, provided plasma Apo-E samples, and underwent diffusion tensor imaging scans. Plasma Apo-E levels and white matter microstructure were analyzed among the MDD with suicidality, MDD without suicidality, and HC groups using analysis of variance with post hoc Bonferroni correction and tract-based spatial statistics (TBSS) with threshold-free cluster enhancement correction. Mediation analysis investigated the relationship between Apo-E, brain white matter, and suicidality in MDD. The MDD with suicidality subgroup had higher depressive and suicide scores, longer disease course, and lower plasma Apo-E levels than MDD without suicidality. TBSS revealed that the MDD non-suicide subgroup showed significantly increased mean diffusivity in the left corticospinal tract and body of the left corpus callosum, as well as increased axial diffusivity in the left anterior corona radiata and the right posterior thalamic radiation compared to the suicidal MDD group. The main finding was that the increased MD of the left corticospinal tract contributed to the elevated suicide score, with Apo-E mediating the effect. Preliminary result that Apo-E's mediating role between the left corticospinal tract and the suicide factor suggests the neuroimmune mechanism of suicide in MDD. The study was registered on ClinicalTrials.gov (NCT03790085).

Introducing neurofilament light chain measure in psychiatry: current evidence, opportunities, and pitfalls

The recent introduction of new-generation immunoassay methods allows the reliable quantification of structural brain markers in peripheral matrices. Neurofilament light chain (NfL), a neuron-specific cytoskeletal component released in extracellular matrices after neuroaxonal impairment, is considered a promising blood marker of active brain pathology. Given its sensitivity to a wide range of neuropathological alterations, NfL has been suggested for the use in clinical practice as a highly sensitive, but unspecific tool to quantify active brain pathology. While large efforts have been put in characterizing its clinical profile in many neurological conditions, NfL has received far less attention as a potential biomarker in major psychiatric disorders. Therefore, we briefly introduce NfL as a marker of neuroaxonal injury, systematically review recent findings on cerebrospinal fluid and blood NfL levels in patients with primary psychiatric conditions and highlight the opportunities and pitfalls. Current evidence suggests an elevation of blood NfL levels in patients with major depression, bipolar disorder, psychotic disorders, anorexia nervosa, and substance use disorders compared to physiological states. However, blood NfL levels strongly vary across diagnostic entities, clinical stage, and patient subgroups, and are influenced by several demographic, clinical, and analytical factors, which require accurate characterization. Potential clinical applications of NfL measure in psychiatry are seen in diagnostic and prognostic algorithms, to exclude neurodegenerative disease, in the assessment of brain toxicity for different pharmacological compounds, and in the longitudinal monitoring of treatment response. The high inter-individual variability of NfL levels and the lack of neurobiological understanding of its release are some of the main current limitations. Overall, this primer aims to introduce researchers and clinicians to NfL measure in the psychiatric field and to provide a conceptual framework for future research directions.