Regional increases of cortical thickness in untreated, first-episode major depressive disorder

Depression vulnerability and gray matter integrity of interoceptive networks in remitted depressed outpatients

BACKGROUND

Interoception, the representation of internal body states, plays an important role in mental health. While functional neuroimaging links Major Depressive Disorder (MDD) relapse vulnerability to stress-induced inhibition of sensorimotor regions, its association with structural changes in interoceptive networks remains unclear.

METHODS

A secondary analysis explored relationships between gray matter volume and relapse vulnerability in remitted MDD patients (N = 85), with two data acquisitions surrounding eight-weeks of prophylactic psychotherapy followed by a two-year follow-up. Participants were randomly assigned to either Cognitive Behavioral Therapy or Mindfulness-Based Cognitive Therapy (MBCT). Mixed-effects models were applied to study the relationships between cortical thickness, time, and intervention type with clinical variables such as relapse status, residual symptoms, and decentering, adjusting for relevant covariates. Analyses were conducted at whole brain levels as well as in pre-defined regions of interest, focusing on sensory regions implicated by prior research.

RESULTS

Relapse was consistently linked to greater cortical thickness in the left superior circular sulcus of the insula and the left anterior occipital sulcus. Residual symptoms correlated with increased cortical thickness in the left insula and right precentral regions, while decentering was linked to reduced thickness in the middle temporal and inferior parietal regions. MBCT participants showed greater cortical thickness increases in the right superior temporal gyrus over time.

CONCLUSIONS

MDD vulnerability was unexpectedly linked to greater cortical thickness in sensory and prefrontal brain regions, suggesting that depression vulnerability may reflect maladaptive skill acquisition. MBCT may promote gray matter growth in the right superior temporal region.

TRIAL REGISTRATION

ClinicalTrials.govNCT01178424.

Prospective Associations Between Structural Brain Development and Onset of Depressive Disorder During Adolescence and Emerging Adulthood

OBJECTIVE

Brain structural alterations are consistently reported in depressive disorders, yet it remains unclear whether these alterations exist prior to disorder onset and thus may reflect a preexisting vulnerability. The authors investigated prospective adolescent neurodevelopmental risk markers for depressive disorder onset, using data from a 15-year longitudinal study.

METHODS

A community sample of 161 adolescents participated in neuroimaging assessments conducted during early (age 12), mid (age 16), and late (age 19) adolescence. Onsets of depressive disorders were assessed for the period spanning early adolescence through emerging adulthood (ages 12-27). Forty-six participants (28 female) experienced a first episode of a depressive disorder during the follow-up period; 83 participants (36 female) received no mental disorder diagnosis. Joint modeling was used to investigate whether brain structure (subcortical volume, cortical thickness, and surface area) or age-related changes in brain structure were associated with the risk of depressive disorder onset.

RESULTS

Age-related increases in amygdala volume (hazard ratio=3.01), and more positive age-related changes (i.e., greater thickening or attenuated thinning) of temporal (parahippocampal gyrus, hazard ratio=3.73; fusiform gyrus, hazard ratio=4.14), insula (hazard ratio=4.49), and occipital (lingual gyrus, hazard ratio=4.19) regions were statistically significantly associated with the onset of depressive disorder.

CONCLUSIONS

Relative increases in amygdala volume and temporal, insula, and occipital cortical thickness across adolescence may reflect disturbances in brain development, contributing to depression onset. This raises the possibility that prior findings of reduced gray matter in clinically depressed individuals instead reflect alterations that are caused by disorder-related factors after onset.

Surface-based analysis of early cortical gyrification and thickness alterations in treatment-Naïve, first-episode depressive patients during emerging adulthood

BACKGROUND

Extensive research, predominantly in adults, has highlighted structural brain variations among patients with major depressive disorder (MDD). However, emerging adults, who undergo significant cortical reshaping and are highly vulnerable to depression, receive relatively little attention, despite reporting a higher prevalence of childhood trauma experiences. This study examines cortical gyrification and thickness in emerging adults with first-episode, treatment-naïve MDD, with the objective of investigating their association with childhood trauma.

METHODS

Eighty-six emerging adults diagnosed with MDD, aged 18 to 25, and eighty-one healthy controls (HCs), underwent T1-MRI scans. We compared the local gyrification index (LGI) and cortical thickness (CT) between the two groups. Subsequently, we examined the relationship between the LGI and CT in clusters showing differences and childhood trauma as well as clinical characteristics in emerging adults with MDD.

RESULTS

Compared to HCs, MDD showed decreased LGI in the bilateral superior frontal cortices (SFC) and CT in the left pericalcarine cortex (PCC), while an increase in CT was observed in the left lateral orbitofrontal cortex (OFC). The reduction in LGI of the right SFC and the decrease in CT of the left PCC are associated with childhood trauma. Notably these brain abnormalities were not significantly associated with depressive and anxiety symptoms, or the duration of illness.

CONCLUSION

Abnormal cortical development observed in emerging adults with first episode depression may act as a predisposing factor for depression, irrespective of clinical manifestations, and may be linked to childhood trauma.

Associations between cerebellum and major psychiatric disorders: a bidirectional Mendelian randomization study

Despite its small size the cerebellum is an anatomically complex and functionally important part of the brain. Previous studies have demonstrated associations between characteristic features/anatomic anomalies of cerebellum and psychiatric disorders. However, the potential causal relationships are unknown. In this study, a bidirectional two-sample Mendelian randomization approach was employed to investigate single nucleotide polymorphism (SNP) heritability and genetic causal associations between 77 imaging derived phenotypes (IDPs) of the cerebellum and major psychiatric disorder, including major depressive disorder (MDD), bipolar disorder (BD), schizophrenia (SCZ) and attention deficit hyperactivity disorder (ADHD). We identified thirty IDPs for which there was evidence of a causal effect on risk of MDD, BD, SCZ and ADHD. For example, 1 s.d. increase in the mean diffusivity (MD) of the left superior cerebellar peduncle was associated with 32% lower odds of BD risk. Reverse MR indicated that psychiatric disorders was associated with fourteen IDPs. For example, MDD were causally associated with three IDPs of gray matter volume (GMV) of right and left X cerebellum, and vermis crus II cerebellum. These results suggested that there were genetic causal associations between psychiatric disorders and certain cerebellum regions, such as the cognitive function of posterior cerebellar lobes and the connection of cerebellar to cerebrum. Further investigations need to enhance prediction and intervention strategies for potential psychiatric disorder risks.

Depression, brain structure and socioeconomic status: A UK Biobank study

BACKGROUND

Depression results from interactions between biological, social, and psychological factors. Literature shows that depression is associated with abnormal brain structure, and that socioeconomic status (SES) is associated with depression and brain structure. However, limited research considers the interaction between each of these factors.

METHODS

Multivariate regression analysis was conducted using UK Biobank data on 39,995 participants to examine the relationship between depression and brain volume in 23 cortical regions for the whole sample and then separated by sex. It then examined whether SES affected this relationship.

RESULTS

Eight out of 23 brain areas had significant negative associations with depression in the whole population. However, these relationships were abolished in seven areas when SES was included in the analysis. For females, three regions had significant negative associations with depression when SES was not included, but only one when it was. For males, lower volume in six regions was significantly associated with higher depression without SES, but this relationship was abolished in four regions when SES was included. The precentral gyrus was robustly associated with depression across all analyses.

LIMITATIONS

Participants with conditions that could affect the brain were not excluded. UK Biobank is not representative of the general population which may limit generalisability. SES was made up of education and income which were not considered separately.

CONCLUSIONS

SES affects the relationship between depression and cortical brain volume. Health practitioners and researchers should consider this when working with imaging data in these populations.

Subtyping drug-free first-episode major depressive disorder based on cortical surface area alterations

BACKGROUND

Major depressive disorder (MDD) is recognized as a complex and heterogeneous metal illness, characterized by diverse clinical symptoms and variable treatment outcomes. Previous studies have repeatedly reported alterations in brain morphology in MDD, but findings vary across sample characteristics. Whether this neurobiological substrate could stratify MDD into more homogeneous clinical subgroups thus improving personalized medicine remains unknown.

METHODS

We included 65 drug-free patients with first-episode MDD and 66 healthy controls (HCs) and collected their structural MRI data. We performed the surface reconstruction and calculated cortical surface area using Freesurfer. The surface area of 34 Gy matter regions in each hemisphere based on the Desikan-Killiany atlas were extracted for each participant and subtyping results were obtained with the Louvain community detection algorithm. The demographic and clinical characteristics were then compared between MDD subgroups.

RESULTS

Two subgroups defined by distinct patterns of cortical surface area were identified in first-episode MDD. Subgroup 1 exhibited a significant reduction in surface area across nearly the entire cortex compared to subgroup 2 and HCs, whereas subgroup 2 demonstrated increased surface area than HCs. Further, subgroup 1 exhibited a higher proportion of females, and higher severity of anxiety symptoms compared to subgroup 2.

LIMITATIONS

The relatively small sample size.

CONCLUSIONS

This study identified two neurobiologically subgroups with distinct alterations in cortical surface area among drug-free patients with first-episode MDD. Our results highlight the promise of in delineating morphological heterogeneity within MDD, particularly in relation to the severity of anxiety symptoms.

Unraveling the causal relationships between depression and brain structural imaging phenotypes: A bidirectional Mendelian Randomization study

BACKGROUND

Previous studies have revealed structural brain abnormalities in individuals with depression, but the causal relationship between depression and brain structure remains unclear.

METHODS

A genetic correlation analysis was conducted using summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 1,265 brain structural imaging-derived phenotypes (IDPs, N = 33,224). Subsequently, a bidirectional two-sample Mendelian Randomization (MR) approach was employed to explore the causal relationships between depression and the IDPs that showed genetic correlations with depression. The main MR results were obtained using the inverse variance weighted (IVW) method, and other MR methods were further employed to ensure the reliability of the findings.

RESULTS

Ninety structural IDPs were identified as being genetically correlated with depression and were included in the MR analyses. The IVW MR results indicated that reductions in the volume of several brain regions, including the bilateral subcallosal cortex, right medial orbitofrontal cortex, and right middle-posterior part of the cingulate cortex, were causally linked to an increased risk of depression. Additionally, decreases in surface area of the right middle temporal visual area, right middle temporal cortex, right inferior temporal cortex, and right middle-posterior part of the cingulate cortex were causally associated with a heightened risk of depression. Validation and sensitivity analyses supported the robustness of these findings. However, no evidence was found for a causal effect of depression on structural IDPs.

CONCLUSIONS

Our findings reveal the causal influence of specific brain structures on depression, providing evidence to consider brain structural changes in the etiology and treatment of depression.

Susceptibility or resilience to childhood peer abuse can be explained by cortical thickness in brain regions involved in emotional regulation

Experiencing peer abuse in childhood can damage mental health, but some people exhibit resilience against these negative outcomes. However, it remains uncertain which specific changes in brain structures are associated with this type of resilience. We categorized 217 participants into three groups: resilience group, susceptibility group, and healthy control group, based on their experiences of peer abuse and mental health problems. They underwent MRI scans to measure cortical thickness in various brain regions of the prefrontal cortex. We employed covariance analysis to compare cortical thickness among these groups. Individuals who resilient to anxiety exhibited smaller cortical thickness in the bilateral inferior frontal gyrus (IFG), and with larger thickness in the right medial orbitofrontal cortex (mOFC), while those resilient to stress was associated with smaller thickness in both the bilateral IFG and bilateral middle frontal gyrus (MFG). These findings deepen our understanding of the neural mechanisms underlying resilience and offer insight into improving individual resilience.

Characterizing the distinct imaging phenotypes, clinical behavior, and genetic vulnerability of brain maturational subtypes in mood disorders

BACKGROUND

Mood disorders are characterized by great heterogeneity in clinical manifestation. Uncovering such heterogeneity using neuroimaging-based individual biomarkers, clinical behaviors, and genetic risks, might contribute to elucidating the etiology of these diseases and support precision medicine.

METHODS

We recruited 174 drug-naïve and drug-free patients with major depressive disorder and bipolar disorder, as well as 404 healthy controls. T1 MRI imaging data, clinical symptoms, and neurocognitive assessments, and genetics were obtained and analyzed. We applied regional gray matter volumes (GMV) and quantile normative modeling to create maturation curves, and then calculated individual deviations to identify subtypes within the patients using hierarchical clustering. We compared the between-subtype differences in GMV deviations, clinical behaviors, cell-specific transcriptomic associations, and polygenic risk scores. We also validated the GMV deviations based subtyping analysis in a replication cohort.

RESULTS

Two subtypes emerged: subtype 1, characterized by increased GMV deviations in the frontal cortex, cognitive impairment, a higher genetic risk for Alzheimer's disease, and transcriptionally associated with Alzheimer's disease pathways, oligodendrocytes, and endothelial cells; and subtype 2, displaying globally decreased GMV deviations, more severe depressive symptoms, increased genetic vulnerability to major depressive disorder and transcriptionally related to microglia and inhibitory neurons. The distinct patterns of GMV deviations in the frontal, cingulate, and primary motor cortices between subtypes were shown to be replicable.

CONCLUSIONS

Our current results provide vital links between MRI-derived phenotypes, spatial transcriptome, genetic vulnerability, and clinical manifestation, and uncover the heterogeneity of mood disorders in biological and behavioral terms.

Functional and structural alterations in different durations of untreated illness in the frontal and parietal lobe in major depressive disorder

Major depressive disorder (MDD) is one of the most disabling illnesses that profoundly restricts psychosocial functions and impairs quality of life. However, the treatment rate of MDD is surprisingly low because the availability and acceptability of appropriate treatments are limited. Therefore, identifying whether and how treatment delay affects the brain and the initial time point of the alterations is imperative, but these changes have not been thoroughly explored. We investigated the functional and structural alterations of MDD for different durations of untreated illness (DUI) using regional homogeneity (ReHo) and voxel-based morphometry (VBM) with a sample of 125 treatment-naïve MDD patients and 100 healthy controls (HCs). The MDD patients were subgrouped based on the DUI, namely, DUI ≤ 1 M, 1 < DUI ≤ 6 M, 6 < DUI ≤ 12 M, and 12 < DUI ≤ 48 M. Subgroup comparison (MDD with different DUIs) was applied to compare ReHo and grey matter volume (GMV) extracted from clusters of regions with significant differences (the pooled MDD patients relative to HCs). Correlations and mediation effects were analysed to estimate the relationships between the functional and structural neuroimaging changes and clinical characteristics. MDD patients exhibited decreased ReHo in the left postcentral gyrus and precentral gyrus and reduced GMV in the left middle frontal gyrus and superior frontal gyrus relative to HCs. The initial functional abnormalities were detected after being untreated for 1 month, whereas this duration was 3 months for GMV reduction. Nevertheless, a transient increase in ReHo was observed after being untreated for 3 months. No significant differences were discovered between HCs and MDD patients with a DUI less than 1 month or among MDD patients with different DUIs in either ReHo or GMV. Longer DUI was related to reduced ReHo with GMV as mediator in MDD patients. We identified disassociated functional and anatomical alterations in treatment-naïve MDD patients at different time points in distinct brain regions at the early stage of the disease. Additionally, we also discovered that GMV mediated the relationship between a longer DUI and diminished ReHo in MDD patients, disclosing the latent deleterious and neuro-progressive implications of DUI on both the structure and function of the brain and indicating the necessity of early treatment of MDD.

Beta-informativeness-diffusion multilayer graph embedding for brain network analysis

Brain network analysis provides essential insights into the diagnosis of brain disease. Integrating multiple neuroimaging modalities has been demonstrated to be more effective than using a single modality for brain network analysis. However, a majority of existing brain network analysis methods based on multiple modalities often overlook both complementary information and unique characteristics from various modalities. To tackle this issue, we propose the Beta-Informativeness-Diffusion Multilayer Graph Embedding (BID-MGE) method. The proposed method seamlessly integrates structural connectivity (SC) and functional connectivity (FC) to learn more comprehensive information for diagnosing neuropsychiatric disorders. Specifically, a novel beta distribution mapping function (beta mapping) is utilized to increase vital information and weaken insignificant connections. The refined information helps the diffusion process concentrate on crucial brain regions to capture more discriminative features. To maximize the preservation of the unique characteristics of each modality, we design an optimal scale multilayer brain network, the inter-layer connections of which depend on node informativeness. Then, a multilayer informativeness diffusion is proposed to capture complementary information and unique characteristics from various modalities and generate node representations by incorporating the features of each node with those of their connected nodes. Finally, the node representations are reconfigured using principal component analysis (PCA), and cosine distances are calculated with reference to multiple templates for statistical analysis and classification. We implement the proposed method for brain network analysis of neuropsychiatric disorders. The results indicate that our method effectively identifies crucial brain regions associated with diseases, providing valuable insights into the pathology of the disease, and surpasses other advanced methods in classification performance.

The Dark and Gloomy Brain: Grey Matter Volume Alterations in Major Depressive Disorder-Fine-Grained Meta-Analyses

Background

While the brain correlates of major depressive disorder (MDD) have been extensively studied, there is no consensus conclusion so far. Various meta-analyses tried to determine the most consistent findings, but the results are often discordant for grey matter volume (GMV) atrophy and hypertrophy. Applying rigorous and stringent inclusion criteria and controlling for confounding factors, such as the presence of anxiety comorbidity, we carried out two novel meta-analyses on the existing literature to unveil MDD signatures.

Methods

A systematic literature search was performed up to January 2023. Seventy-three studies on MDD patients reporting GMV abnormalities were included in the first meta-analysis, for a total of 6167 patients and 6237 healthy controls (HC). To test the effects of anxiety comorbidity, we conducted a second meta-analysis, by adding to the original pure MDD sample a new cohort of MDD patients with comorbid anxiety disorders (308 patients and 342 HC). An activation likelihood estimation (ALE) analysis and a coordinate-based mapping approach separate for atrophy and hypertrophy were used to identify common brain structural alterations among patients.

Results

The pure MDD sample exhibited atrophy in the left insula, as well as hypertrophy in the bilateral amygdala and parahippocampal gyri. When we added patients with comorbid anxiety to the original sample, bilateral insula atrophy emerged, whereas the hypertrophy results were not replicated.

Conclusions

Our findings revealed important structural alterations in pure MDD patients, particularly in the insula and amygdala, which play key roles in sensory input integration and in emotional processing, respectively. Additionally, the amygdala and parahippocampal gyrus hypertrophy may be related to MDD functional overactivation to emotional stimuli, rumination, and overactive self-referential thinking. Conversely, the presence of anxiety comorbidity revealed separate effects which were not seen in the pure MDD sample, underscoring the importance of strict inclusion criteria for investigations of disorder-specific effects.

Cortical thickness reductions associate with brain network architecture in major depressive disorder

BACKGROUND

Cortical thickness reductions in major depressive disorder are distributed across multiple regions. Research has indicated that cortical atrophy is influenced by connectome architecture on a range of neurological and psychiatric diseases. However, whether connectome architecture contributes to changes in cortical thickness in the same manner as it does in depression is unclear. This study aims to explain the distribution of cortical thickness reductions across the cortex in depression by brain connectome architecture.

METHODS

Here, we calculated a differential map of cortical thickness between 110 depression patients and 88 age-, gender-, and education level-matched healthy controls by using T1-weighted images and a structural network reconstructed through the diffusion tensor imaging of control group. We then used a neighborhood deformation model to explore how cortical thickness change in an area is influenced by areas structurally connected to it.

RESULTS

We found that cortical thickness in the frontoparietal and default networks decreased in depression, regional cortical thickness changes were related to reductions in their neighbors and were mainly limited by the frontoparietal and default networks, and the epicenter was in the prefrontal lobe.

CONCLUSION

Current findings suggest that connectome architecture contributes to the irregular topographic distribution of cortical thickness reductions in depression and cortical atrophy is restricted by and dependent on structural foundation.

Regional decreases of cortical thickness in major depressive disorder and their correlation with illness duration: a case-control study

Background

Alterations in brain structure and function in major depressive disorder (MDD) have been identified in a number of studies, but findings regarding cortical thickness were various and inconsistent. Our current study aims to explore the differences in cortical thickness between individuals with MDD and healthy controls (HC) in a Chinese population.

Methods

We investigated T1-weighted brain magnetic resonance imaging data from 61 participants (31 MDD and 30 HC). The cortical thickness between the two groups and analyzed correlations between cortical thickness and demographic variables in the MDD group for regions with significant between-group differences were conducted.

Results

Compared with the HC group, patients with MDD had significantly decreased cortical thickness, in left pars triangularis, left pars orbitalis, left rostral middle frontal gyrus, left supramarginal gyrus, right parahippocampal gyrus, right lingual gyrus, right fusiform and right inferior parietal gyrus. The cortical thickness of left rostral middle frontal gyrus was negatively correlated (r = -0.47, p = 0.028) with the illness duration in patients with MDD.

Conclusion

Our study distinguished that cortical thickness decreases in numerous brain regions both in the left and right hemisphere in individuals with MDD, and the negative correlation between the cortical thickness of left rostral middle frontal gyrus illness duration. Our current findings are valuable in providing neural markers to identify MDD and understanding the potential pathophysiology of mood disorders.

Neuroanatomical dimensions in medication-free individuals with major depressive disorder and treatment response to SSRI antidepressant medications or placebo

Major depressive disorder (MDD) is a heterogeneous clinical syndrome with widespread subtle neuroanatomical correlates. Our objective was to identify the neuroanatomical dimensions that characterize MDD and predict treatment response to selective serotonin reuptake inhibitor (SSRI) antidepressants or placebo. In the COORDINATE-MDD consortium, raw MRI data were shared from international samples (N = 1,384) of medication-free individuals with first-episode and recurrent MDD (N = 685) in a current depressive episode of at least moderate severity, but not treatment-resistant depression, as well as healthy controls (N = 699). Prospective longitudinal data on treatment response were available for a subset of MDD individuals (N = 359). Treatments were either SSRI antidepressant medication (escitalopram, citalopram, sertraline) or placebo. Multi-center MRI data were harmonized, and HYDRA, a semi-supervised machine-learning clustering algorithm, was utilized to identify patterns in regional brain volumes that are associated with disease. MDD was optimally characterized by two neuroanatomical dimensions that exhibited distinct treatment responses to placebo and SSRI antidepressant medications. Dimension 1 was characterized by preserved gray and white matter (N = 290 MDD), whereas Dimension 2 was characterized by widespread subtle reductions in gray and white matter (N = 395 MDD) relative to healthy controls. Although there were no significant differences in age of onset, years of illness, number of episodes, or duration of current episode between dimensions, there was a significant interaction effect between dimensions and treatment response. Dimension 1 showed a significant improvement in depressive symptoms following treatment with SSRI medication (51.1%) but limited changes following placebo (28.6%). By contrast, Dimension 2 showed comparable improvements to either SSRI (46.9%) or placebo (42.2%) (β = -18.3, 95% CI (-34.3 to -2.3), P = 0.03). Findings from this case-control study indicate that neuroimaging-based markers can help identify the disease-based dimensions that constitute MDD and predict treatment response.

Hippocampal volume and resting-state functional connectivity on magnetic resonance imaging in patients with Parkinson and depression

Background

Recent structural and functional imaging studies of depression in Parkinson disease (DPD) have failed to reveal the relevant mechanism, and relatively few studies have been conducted on limbic systems such as the hippocampus. This study thus aimed to gain new insights into the pathogenesis of DPD by detecting the changes in the hippocampal structure and the resting-state functional connectivity (FC) of patients with DPD.

Methods

This study included 30 patients with DPD (DPD group), 30 patients with nondepressed Parkinson disease (NDPD; NDPD group), and 30 normal controls (NCs; NC group) with no significant age or gender differences with the DPD group. The Hamilton Depression Rating Scale (HAMD) and three-dimensional T1-weighted imaging and blood oxygen level-dependent imaging data of all patients were collected. The hippocampal volumes were measured using MATLAB software (MathWorks). The correlation between hippocampal volume and the HAMD score in the DPD group was analyzed with Pearson correlation coefficient. The bilateral hippocampi were used as the regions of interest and as the seed points for FC. FC analysis was performed between the preprocessed functional data of the whole brain and the two seed points with Data Processing Assistant for Resting-State and Statistical Parametric Mapping 8 software, respectively. The correlation between FC and HAMD scores in the patients with DPD was determined using partial correlation analysis.

Results

Compared with those in the NC group and the NDPD group, the bilateral hippocampal volumes in the DPD group were significantly decreased (P<0.05). There was a negative correlation between the bilateral hippocampal volume and the HAMD score in the DPD group (P<0.05). Compared with that of the NDPD group, the FC of the right hippocampus with the right occipital lobe and left precuneus was reduced in the DPD group. In the DPD group, the FC values of the right hippocampus, right occipital lobe, and left anterior cuneiform lobe were negatively correlated with HAMD scores.

Conclusions

The volume of bilateral hippocampi in patients with DPD is significantly decreased and negatively correlated with the severity of depressive disorder. The weakened FC of the right hippocampus to the right occipital lobe and the left precuneus may play an important role in the neurological basis of DPD.

Orbitofrontal and striatal metabolism, volume, thickness and structural connectivity in relation to social anhedonia in depression: A multimodal study

BACKGROUND

Social anhedonia is common within major depressive disorder (MDD) and associated with worse treatment outcomes. The orbitofrontal cortex (OFC) is implicated in both reward (medial OFC) and punishment (lateral OFC) in social decision making. Therefore, to understand the biology of social anhedonia in MDD, medial/lateral OFC metabolism, volume, and thickness, as well as structural connectivity to the striatum, amygdala, and ventral tegmental area/nucleus accumbens were examined. A positive relationship between social anhedonia and these neurobiological outcomes in the lateral OFC was hypothesized, whereas an inverse relationship was hypothesized for the medial OFC. The association between treatment-induced changes in OFC neurobiology and depression improvement were also examined.

METHODS

85 medication-free participants diagnosed with MDD were assessed with Wisconsin Schizotypy Scales to assess social anhedonia and received pretreatment simultaneous fluorodeoxyglucose positron emission tomography (FDG-PET) and magnetic resonance imaging (MRI), including structural and diffusion. Participants were then treated in an 8-week randomized placebo-controlled double-blind course of escitalopram. PET/MRI were repeated following treatment. Metabolic rate of glucose uptake was quantified from dynamic FDG-PET frames using Patlak graphical analysis. Structure (volume and cortical thickness) was quantified from structural MRI using Freesurfer. To assess structural connectivity, probabilistic tractography was performed on diffusion MRI and average FA was calculated within the derived tracts. Linear mixed models with Bonferroni correction were used to examine the relationships between variables.

RESULTS

A significantly negative linear relationship between pretreatment social anhedonia score and structural connectivity between the medial OFC and the amygdala (estimated coefficient: -0.006, 95 % CI: -0.0108 - -0.0012, p-value = 0.0154) was observed. However, this finding would not survive multiple comparisons correction. No strong evidence existed to show a significant linear relationship between pretreatment social anhedonia score and metabolism, volume, thickness, or structural connectivity to any of the regions examined. There was also no strong evidence to suggest significant linear relationships between improvement in depression and percent change in these variables.

CONCLUSIONS

Based on these multimodal findings, the OFC likely does not underlie social anhedonia in isolation and therefore should not be the sole target of treatment for social anhedonia. This is consistent with previous reports that other areas of the brain such as the amygdala and the striatum are highly involved in this behavior. Relatedly, amygdala-medial OFC structural connectivity could be a future target. The results of this study are crucial as, to our knowledge, they are the first to relate structure/function of the OFC with social anhedonia severity in MDD. Future work may need to involve a whole brain approach in order to develop therapeutics for social anhedonia.

Repetitive Negative Thinking-Specific and -Nonspecific White Matter Tracts Engaged by Historical Psychosurgical Targets for Depression

BACKGROUND

Repetitive negative thinking (RNT) is a frequent symptom of major depressive disorder (MDD) that is associated with poor outcomes and treatment resistance. While most studies on RNT have focused on structural and functional characteristics of gray matter, this study aimed to examine the association between white matter (WM) tracts and interindividual variability in RNT.

METHODS

A probabilistic tractography approach was used to characterize differences in the size and anatomical trajectory of WM fibers traversing psychosurgery targets historically useful in the treatment of MDD (anterior capsulotomy, anterior cingulotomy, and subcaudate tractotomy) in patients with MDD and low (n = 53) or high (n = 52) RNT, and healthy control subjects (n = 54). MDD samples were propensity matched on depression and anxiety severity and demographics.

RESULTS

WM tracts traversing left hemisphere targets and reaching the ventral anterior body of the corpus callosum (thus extending to contralateral regions) were larger in the high-RNT MDD group compared with low-RNT (effect size D = 0.27, p = .042) and healthy control (D = 0.23, p = .02) groups. MDD was associated with greater size of tracts that converge onto the right medial orbitofrontal cortex regardless of RNT intensity. Other RNT-nonspecific findings in MDD involved tracts reaching the left primary motor and right primary somatosensory cortices.

CONCLUSIONS

This study provides the first evidence to our knowledge that WM connectivity patterns, which could become targets of intervention, differ between high- and low-RNT participants with MDD. These WM differences extend to circuits that are not specific to RNT, possibly subserving reward mechanisms and psychomotor activity.

Disrupted brain gray matter connectome in social anxiety disorder: a novel individualized structural covariance network analysis

Phenotyping approaches grounded in structural network science can offer insights into the neurobiological substrates of psychiatric diseases, but this remains to be clarified at the individual level in social anxiety disorder (SAD). Using a recently developed approach combining probability density estimation and Kullback-Leibler divergence, we constructed single-subject structural covariance networks (SCNs) based on multivariate morphometry (cortical thickness, surface area, curvature, and volume) and quantified their global/nodal network properties using graph-theoretical analysis. We compared network metrics between SAD patients and healthy controls (HC) and analyzed the relationship to clinical characteristics. We also used support vector machine analysis to explore the ability of graph-theoretical metrics to discriminate SAD patients from HC. Globally, SAD patients showed higher global efficiency, shorter characteristic path length, and stronger small-worldness. Locally, SAD patients showed abnormal nodal centrality mainly involving left superior frontal gyrus, right superior parietal lobe, left amygdala, right paracentral gyrus, right lingual, and right pericalcarine cortex. Altered topological metrics were associated with the symptom severity and duration. Graph-based metrics allowed single-subject classification of SAD versus HC with total accuracy of 78.7%. This finding, that the topological organization of SCNs in SAD patients is altered toward more randomized configurations, adds to our understanding of network-level neuropathology in SAD.

Common and exclusive spontaneous neural activity patterns underlying pure generalized anxiety disorder and comorbid generalized anxiety disorder and depression

BACKGROUND

This study aimed to identify common and exclusive neural substrates underlying pure generalized anxiety disorder (GAD, G0) and comorbid GAD and depression (G1), assess whether they could assist in diagnosis and prediction of treatment response, and determine whether comorbid depression in GAD patients would change their neural plasticity.

METHODS

A longitudinal study was conducted, involving 98 patients (40 in the G0 group and 58 in the G1 group) and 54 healthy controls (HCs). The fractional amplitude of low-frequency fluctuations (fALFF), support vector machine, and support vector regression were employed.

RESULTS

The shared neural underpinnings across the two subtypes of GAD were hyperactivity in the right cerebellar Crus II and inferior temporal gyrus and hypoactivity in the right postcentral gyrus. The G1 group showed hypoactivity in the frontal gyrus, compared with HCs, and hyperactivity in the middle temporal gyrus, compared with the G0 group or HCs. These alterations could aid in diagnosis and the prediction of treatment response with high accuracy. After treatment, both the G1 and G0 groups showed higher fALFF than those before treatment but were located in different brain regions.

LIMITATIONS

The study was performed in a single center and subjects showed a fairly homogeneous ethnicity.

CONCLUSIONS

Common and exclusive neural substrates underlying the two subtypes of GAD were identified, which could assist in diagnosis and the prediction of treatment response. Pharmacotherapy for the two subtypes of GAD recruited different pathways, suggesting that comorbid depression in GAD patients would change their neural plasticity.

Cortical and subcortical morphological alterations in postpartum depression

Postpartum depression (PPD) is the most common postpartum psychiatric disorder, which can negatively affect both mothers and their offspring. Although the functional changes of PPD have been extensively studied, little is known about its structural abnormalities. This study aimed to examine the cortical and subcortical morphological abnormalities in PPD. High resolution T1 structural MRI data of 29 PPD women and 23 matched healthy postpartum women (HPW) were included in this study. Using surface-based morphometry, we examined the differences between the PPD and HPW group in the cortical thickness, local gyrification index and shape changes of deep gray matter nuclei. Compared with the HPW group, women with PPD showed significantly increased cortical thickness in the left superior frontal gyrus, cuneus and right lingual gyrus and fusiform gyrus, which correlated marginally with the EPDS scores of these subjects. In addition, women with PPD showed significant regional inflation in the right pallidum compared with the HPW group. These findings provided further evidence for the structural brain abnormalities in PPD.

10-Year trajectories of depressive symptoms and subsequent brain health in middle-aged adults

Depressive symptoms differ in severity and stability over time. Trajectories depicting these changes, particularly those with high late-life depressive symptoms, have been associated with poor brain health at old age. To better understand these associations across the lifespan, we examined depressive symptoms trajectories in relation to brain health in middle age. We included 1676 participants from the ORACLE Study, all were expecting a child at baseline (mean age 32.8, 66.6% women). Depressive symptoms were assessed at baseline, 3 years and 10 years after baseline. Brain health (global brain volume, subcortical structures volume, white matter lesions, cerebral microbleeds, cortical thickness, cortical surface area) was assessed 15 years after baseline. Using k-means clustering, four depressive symptoms trajectories were identified: low, low increasing, decreasing, and high increasing symptoms. The high increasing trajectory was associated with smaller brain volume compared to low symptoms, not surviving multiple testing correction. The low increasing trajectory was associated with more cortical thickness in a small region encompassing the right lateral occipital cortex compared to low symptoms. These findings show that longitudinal depressive symptoms trajectories are only minimally associated with brain health in middle age, suggesting that associations may only emerge later in life.

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

BACKGROUND

Morphometric studies demonstrated wide-ranging distribution of brain structural abnormalities in major depressive disorder (MDD).

OBJECTIVE

This study explored the progressive gray matter volume (GMV) changes pattern of structural network in 108 MDD patients throughout the illness duration by using voxel-based morphometric analysis.

METHODS

The causal structural covariance network method was applied to map the causal effects of GMV alterations between the original source of structural changes and other brain regions as the illness duration prolonged in MDD. This was carried out by utilizing the Granger causality analysis to T1-weighted data ranked based on the disease progression information.

RESULTS

With greater illness duration, the GMV reduction was originated from the right insula and progressed to the frontal lobe, and then expanded to the occipital lobe, temporal lobe, dorsal striatum (putamen and caudate) and the cerebellum. Importantly, results revealed that the right insula was the prominent node projecting positive causal influences (i.e., GMV decrease) to frontal lobe, temporal lobe, postcentral gyrus, putamen, and precuneus. While opposite causal effects were detected from the right insula to the angular, parahippocampus, supramarginal gyrus and cerebellum.

CONCLUSIONS

This work may provide further information and vital evidence showing that MDD is associated with progressive brain structural alterations.

Mild behavioral impairment linked to progression to Alzheimer's disease and cortical thinning in amnestic mild cognitive impairment

Background

Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of sustained neuropsychiatric symptoms, as an at-risk state for dementia. However, the associations between MBI and a risk of progression to Alzheimer's disease (AD) and its neuroanatomical correlates in mild cognitive impairment (MCI) are still unclear.

Method

A total 1,184 older adults with amnestic MCI was followed for a mean of 3.1 ± 2.0 years. MBI was approximated using a transformation algorithm for the Neuropsychiatric Inventory at baseline. A two-step cluster analysis was used to identify subgroups of individuals with amnestic MCI based on profiles of 5 MBI domain symptoms (decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, abnormal perception/thought content). A Cox regression analysis was applied to investigate differences in the risk of progression to AD between subgroups. A subset of participants (n = 202) underwent 3D T1-weighted MRI scans at baseline and cortical thickness was compared between the subgroups of amnestic MCI patients.

Result

The cluster analysis classified the patients into 3 groups: (1) patients without any MBI domain symptoms (47.4%, asymptomatic group); (2) those with only affective dysregulation (29.4%, affective dysregulation group); (3) those with multiple MBI domain symptoms, particularly affective dysregulation, decreased motivation and impulse dyscontrol (23.2%, complex group). Compared to the asymptomatic group, the complex group was associated with a higher risk of progression to AD (hazard ratio = 2.541 [1.904-3.392], p < 0.001), but the affective dysregulation group was not (1.214 [0.883-1.670], p = 0.232). In cortical thickness analysis, the complex group revealed cortical thinning bilaterally in the inferior parietal, lateral occipital, lateral superior temporal, and frontopolar regions compared with the affective dysregulation group.

Conclusion

The multiple co-occuring MBI domains in individuals with amnestic MCI are associated with a higher risk of progression to AD and cortical thinning in temporal, parietal and frontal areas. These results suggest that evaluation of MBI could be useful for risk stratification for AD and appropriate intervention in MCI individuals.

Severity related neuroanatomical and spontaneous functional activity alteration in adolescents with major depressive disorder

Background

Major depressive disorder (MDD) is a disabling and severe psychiatric disorder with a high rate of prevalence, and adolescence is one of the most probable periods for the first onset. The neurobiological mechanism underlying the adolescent MDD remains unexplored.

Methods

In this study, we examined the cortical and subcortical alterations of neuroanatomical structures and spontaneous functional activation in 50 unmedicated adolescents with MDD vs. 39 healthy controls through the combined structural and resting-state functional magnetic resonance imaging.

Results

Significantly altered regional gray matter volume was found at broader frontal-temporal-parietal and subcortical brain areas involved with various forms of information processing in adolescent MDD. Specifically, the increased GM volume at the left paracentral lobule and right supplementary motor cortex was significantly correlated with depression severity in adolescent MDD. Furthermore, lower cortical thickness at brain areas responsible for visual and auditory processing as well as motor movements was found in adolescent MDD. The lower cortical thickness at the superior premotor subdivision was positively correlated with the course of the disease. Moreover, higher spontaneous neuronal activity was found at the anterior cingulum and medial prefrontal cortex, and this hyperactivity was also negatively correlated with the course of the disease. It potentially reflected the rumination, impaired concentration, and physiological arousal in adolescent MDD.

Conclusion

The abnormal structural and functional findings at cortico-subcortical areas implied the dysfunctional cognitive control and emotional regulations in adolescent depression. The findings might help elaborate the underlying neural mechanisms of MDD in adolescents.

Brain structure and connectivity in psoriasis and associations with depression and inflammation; findings from the UK biobank

Background

Psoriasis is a chronic systemic inflammatory skin disease, coexisting with depression in up to 25% of patients. Little is known about the drivers of comorbidity, including shared neurobiology and depression brain imaging patterns in patients. An immune-mediated crosstalk between the brain and skin has been hypothesized in psoriasis. With the aim of investigating brain structure and connectivity in psoriasis in relation to depression comorbidity, we conducted a brain imaging study including the largest psoriasis patient sample to date (to our knowledge) and the first to investigate the role of depression and systemic inflammation in brain measures. Effects of coexisting psoriatic arthritis (PsA), which represents joint involvement in psoriasis and a higher putative inflammatory state, were further explored.

Methods

Brain magnetic resonance imaging (MRI) data of 1,048 UK Biobank participants were used (131 comorbid patients with psoriasis and depression, age-and sex-matched to: 131 non-depressed psoriasis patients; 393 depressed controls; and 393 non-depressed controls). Interaction effects of psoriasis and depression on volume, thickness and surface of a-priori defined regions of interest (ROIs), white matter tracts and 55x55 partial correlation resting-state connectivity matrices were investigated using general linear models. Linear regression was employed to test associations of brain measures with C-reactive protein (CRP) and neutrophil counts.

Results

No differences in regional or global brain volumes or white matter integrity were found in patients with psoriasis compared to controls without psoriasis or PsA. Thickness in right precuneus was increased in psoriasis patients compared to controls, only when depression was present (β = 0.26, 95% CI [Confidence Intervals] 0.08, 0.44; p = 0.02). In further analysis, psoriasis patients who had PsA exhibited fronto-occipital decoupling in resting-state connectivity compared to patients without joint involvement (β = 0.39, 95% CI 0.13, 0.64; p = 0.005) and controls (β = 0.49, 95% CI 0.25, 0.74; p < 0.001), which was unrelated to depression comorbidity. Precuneus thickness and fronto-occipital connectivity were not predicted by CRP or neutrophil counts. Precuneus thickening among depressed psoriasis patients showed a marginal correlation with recurrent lifetime suicidality.

Conclusions

Our findings provide evidence for a combined effect of psoriasis and depression on the precuneus, which is not directly linked to systemic inflammation, and may relate to suicidality or altered somatosensory processing. The use of the UK Biobank may limit generalizability of results in populations with severe disease.

Prenatal exposure to air pollution is associated with altered brain structure, function, and metabolism in childhood

BACKGROUND

Prenatal exposure to air pollution disrupts cognitive, emotional, and behavioral development. The brain disturbances associated with prenatal air pollution are largely unknown.

METHODS

In this prospective cohort study, we estimated prenatal exposures to fine particulate matter (PM_2.5 ) and polycyclic aromatic hydrocarbons (PAH), and then assessed their associations with measures of brain anatomy, tissue microstructure, neurometabolites, and blood flow in 332 youth, 6-14 years old. We then assessed how those brain disturbances were associated with measures of intelligence, ADHD and anxiety symptoms, and socialization.

RESULTS

Both exposures were associated with thinning of dorsal parietal cortices and thickening of postero-inferior and mesial wall cortices. They were associated with smaller white matter volumes, reduced organization in white matter of the internal capsule and frontal lobe, higher metabolite concentrations in frontal cortex, reduced cortical blood flow, and greater microstructural organization in subcortical gray matter nuclei. Associations were stronger for PM_2.5 in boys and PAH in girls. Youth with low exposure accounted for most significant associations of ADHD, anxiety, socialization, and intelligence measures with cortical thickness and white matter volumes, whereas it appears that high exposures generally disrupted these neurotypical brain-behavior associations, likely because strong exposure-related effects increased the variances of these brain measures.

CONCLUSIONS

The commonality of effects across exposures suggests PM_2.5 and PAH disrupt brain development through one or more common molecular pathways, such as inflammation or oxidative stress. Progressively higher exposures were associated with greater disruptions in local volumes, tissue organization, metabolite concentrations, and blood flow throughout cortical and subcortical brain regions and the white matter pathways interconnecting them. Together these affected regions comprise cortico-striato-thalamo-cortical circuits, which support the regulation of thought, emotion, and behavior.

Altered spontaneous brain activity in major depressive disorder: An activation likelihood estimation meta-analysis

BACKGROUND

Wide application of resting-state functional magnetic resonance imaging (fMRI) in psychiatric research has revealed that major depressive disorder (MDD) manifest abnormal neural activities in several brain regions involving key resting state networks. However, inconsistent results have hampered our understanding of the exact neuropathology associated with MDD. Therefore, our aim was to conduct a meta-analysis to identify the consistent vulnerable brain regions of MDD in resting state, and to reveal the potential pathogenesis of MDD.

METHODS

A systematic review analysis was conducted on studies involving brain resting-state changes in MDD using low-frequency amplitude (ALFF), fractional low-frequency amplitude (fALFF) and regional homogeneity (ReHo) analysis. The meta-analysis was based on the activation likelihood estimation method, using the software of Ginger ALE 2.3.

RESULTS

25 studies (892 MDD and 799 healthy controls) were included. Based on the meta-analysis results of ReHo, we found robust reduction of resting-state spontaneous brain activity in MDD, including the left cuneus and right middle occipital gyrus (cluster size = 216, 256 mm³, uncorrected P < 0.0001), while no increased spontaneous activation in any of the brain regions. We also found reduced ALFF in the left middle occipital gyrus (cluster size = 224 mm³, uncorrected P < 0.0001), and no increased spontaneous brain activation in any regions.

CONCLUSION

Our meta-analysis study using the activation likelihood estimation method demonstrated that MDD showed significant abnormalities in spontaneous neural activity, compared with healthy controls, mainly in areas associated with visual processing, such as the cuneus and the middle occipital gyrus. Dysfunction of these brain regions may be one of the pathogenesis of MDD.

Gray and white matter structural examination for diagnosis of major depressive disorder and subthreshold depression in adolescents and young adults: a preliminary radiomics analysis

BACKGROUND

Radiomics is an emerging image analysis framework that provides more details than conventional methods. In present study, we aimed to identify structural radiomics features of gray matter (GM) and white matter (WM), and to develop and validate the classification model for major depressive disorder (MDD) and subthreshold depression (StD) diagnosis using radiomics analysis.

METHODS

A consecutive cohort of 142 adolescents and young adults, including 43 cases with MDD, 49 cases with StD and 50 healthy controls (HC), were recruited and underwent the three-dimensional T1 weighted imaging (3D-T1WI) and diffusion tensor imaging (DTI). We extracted radiomics features representing the shape and diffusion properties of GM and WM from all participants. Then, an all-relevant feature selection process embedded in a 10-fold cross-validation framework was used to identify features with significant power for discrimination. Random forest classifiers (RFC) were established and evaluated successively using identified features.

RESULTS

The results showed that a total of 3030 features were extracted after preprocessing, including 2262 shape-related features from each T1-weighted image representing GM morphometry and 768 features from each DTI representing the diffusion properties of WM. 25 features were selected ultimately, including ten features for MDD versus HC, eight features for StD versus HC, and seven features for MDD versus StD. The accuracies and area under curve (AUC) the RFC achieved were 86.75%, 0.93 for distinguishing MDD from HC with significant radiomics features located in the left medial orbitofrontal cortex, right superior and middle temporal regions, right anterior cingulate, left cuneus and hippocampus, 70.51%, 0.69 for discriminating StD from HC within left cuneus, medial orbitofrontal cortex, cerebellar vermis, hippocampus, anterior cingulate and amygdala, right superior and middle temporal regions, and 59.15%, 0.66 for differentiating MDD from StD within left medial orbitofrontal cortex, middle temporal and cuneus, right superior frontal, superior temporal regions and hippocampus, anterior cingulate, respectively.

CONCLUSION

These findings provide preliminary evidence that radiomics features of brain structure are valid for discriminating MDD and StD subjects from healthy controls. The MRI-based radiomics approach, with further improvement and validation, might be a potential facilitating method to clinical diagnosis of MDD or StD.

Personalized Diagnosis and Treatment for Neuroimaging in Depressive Disorders

Depressive disorders are highly heterogeneous in nature. Previous studies have not been useful for the clinical diagnosis and prediction of outcomes of major depressive disorder (MDD) at the individual level, although they provide many meaningful insights. To make inferences beyond group-level analyses, machine learning (ML) techniques can be used for the diagnosis of subtypes of MDD and the prediction of treatment responses. We searched PubMed for relevant studies published until December 2021 that included depressive disorders and applied ML algorithms in neuroimaging fields for depressive disorders. We divided these studies into two sections, namely diagnosis and treatment outcomes, for the application of prediction using ML. Structural and functional magnetic resonance imaging studies using ML algorithms were included. Thirty studies were summarized for the prediction of an MDD diagnosis. In addition, 19 studies on the prediction of treatment outcomes for MDD were reviewed. We summarized and discussed the results of previous studies. For future research results to be useful in clinical practice, ML enabling individual inferences is important. At the same time, there are important challenges to be addressed in the future.

The role of educational attainment and brain morphology in major depressive disorder: Findings from the ENIGMA major depressive disorder consortium

Brain structural abnormalities and low educational attainment are consistently associated with major depressive disorder (MDD), yet there has been little research investigating the complex interaction of these factors. Brain structural alterations may represent a vulnerability or differential susceptibility marker, and in the context of low educational attainment, predict MDD. We tested this moderation model in a large multisite sample of 1958 adults with MDD and 2921 controls (aged 18 to 86) from the ENIGMA MDD working group. Using generalized linear mixed models and within-sample split-half replication, we tested whether brain structure interacted with educational attainment to predict MDD status. Analyses revealed that cortical thickness in a number of occipital, parietal, and frontal regions significantly interacted with education to predict MDD. For the majority of regions, models suggested a differential susceptibility effect, whereby thicker cortex was more likely to predict MDD in individuals with low educational attainment, but less likely to predict MDD in individuals with high educational attainment. Findings suggest that greater thickness of brain regions subserving visuomotor and social-cognitive functions confers susceptibility to MDD, dependent on level of educational attainment. Longitudinal work, however, is ultimately needed to establish whether cortical thickness represents a preexisting susceptibility marker. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Association of DNA Methylation of the NLRP3 Gene with Changes in Cortical Thickness in Major Depressive Disorder

The Nod-like receptor pyrin containing 3 (NLRP3) inflammasome has been reported to be a convergent point linking the peripheral immune response induced by psychological stress and neuroinflammatory processes in the brain. We aimed to identify differences in the methylation profiles of the NLRP3 gene between major depressive disorder (MDD) patients and healthy controls (HCs). We also investigated the correlation of the methylation score of loci in NLRP3 with cortical thickness in the MDD group using magnetic resonance imaging (MRI) data. A total of 220 patients with MDD and 82 HCs were included in the study, and genome-wide DNA methylation profiling of the NLRP3 gene was performed. Among the total sample, 88 patients with MDD and 74 HCs underwent T1-weighted structural MRI and were included in the neuroimaging–methylation analysis. We identified five significant differentially methylated positions (DMPs) in NLRP3. In the MDD group, the methylation scores of cg18793688 and cg09418290 showed significant positive or negative correlations with cortical thickness in the occipital, parietal, temporal, and frontal regions, which showed significant differences in cortical thickness between the MDD and HC groups. Our findings suggest that NLRP3 DNA methylation may predispose to depression-related brain structural changes by increasing NLRP3 inflammasome-related neuroinflammatory processes in MDD.

Brain temperature as an indicator of neuroinflammation induced by typhoid vaccine: Assessment using whole-brain magnetic resonance spectroscopy in a randomised crossover study

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MRSI-derived whole-brain temperature did not detect low-level neuroinflammation.

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Regional brain temperature was a more sensitive measure of neuroinflammation.

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MRSI/EPSI might be a useful measure of neuroinflammation in psychiatric disorders.

Prior studies indicate a pathogenic role of neuroinflammation in psychiatric disorders; however, there are no accepted methods that can reliably measure low-level neuroinflammation non-invasively in these individuals. Magnetic resonance spectroscopic imaging (MRSI) is a versatile, non-invasive neuroimaging technique that demonstrates sensitivity to brain inflammation. MRSI in conjunction with echo-planar spectroscopic imaging (EPSI) measures brain metabolites to derive whole-brain and regional brain temperatures, which may increase in neuroinflammation. The validity of MRSI/EPSI for measurement of low level neuroinflammation was tested using a safe experimental model of human brain inflammation – intramuscular administration of typhoid vaccine. Twenty healthy volunteers participated in a double-blind, placebo-controlled crossover study including MRSI/EPSI scans before and 3 h after vaccine/placebo administration. Body temperature and mood, assessed using the Profile of Mood States, were measured every hour up to four hours post-treatment administration. A mixed model analysis of variance was used to test for treatment effects. A significant proportion of brain regions (44/47) increased in temperature post-vaccine compared to post-placebo (p < 0.0001). For temperature change in the brain as a whole, there was no significant treatment effect. Significant associations were seen between mood scores assessed at 4 h and whole brain and regional temperatures post-treatment. Findings indicate that regional brain temperature may be a more sensitive measure of low-level neuroinflammation than whole-brain temperature. Future work where these measurement techniques are applied to populations with psychiatric disorders would be of clinical interest.

Stimulation of the dorsolateral prefrontal cortex modulates muscle sympathetic nerve activity and blood pressure in humans

Introduction

Muscle sympathetic nerve activity (MSNA) controls the diameter of arterioles in skeletalmuscle, contributing importantly to the beat-to-beat regulation of blood pressure (BP). Although brain imaging studies have shown that bursts of MSNA originate in the rostral ventrolateral medulla, other subcortical and cortical structures-including the dorsolateral prefrontal cortex (dlPFC)-contribute.

Hypothesis

We tested the hypothesis that MSNA and BP could be modulated by stimulating the dlPFC.

Method

dlPFC. In 22 individuals MSNA was recorded via microelectrodes inserted into the common peroneal nerve, together with continuous BP, electrocardiographic, and respiration.Stimulation of the right (n=22) or left dlPFC (n=10) was achieved using transcranial alternating current (tcACS; +2 to -2mA, 0.08 Hz,100 cycles), applied between the nasion and electrodes over the F3 or F4 EEG sites on the scalp.

Results

Sinusoidal stimulation of either dlPFC caused cyclicmodulation of MSNA, BP and heart rate, and a significant increase in BP.

Conclusion

We have shown, for the first time, that tcACS of the dlPFC in awake humans causes partial entrainment of MSNA, heart rate and BP, arguing for an important role of this higher-level cortical area in the control of cardiovascular function.

Neuroimaging of psychiatric disorders

Psychiatry remains the only medical specialty where diagnoses are still based on clinical syndromes rather than measurable biological abnormalities. As imaging technology and analytical methods evolve, it is becoming clear that subtle but measurable radiological characteristics exist and can be used to experimentally classify psychiatric disorders, predict response to treatment and, hopefully, develop new, more effective therapies. This review highlights advances in neuroimaging modalities that are now allowing assessment of brain structure, connectivity and neural network function, describes technical aspects of the most promising methods, and summarizes observations made in some frequent psychiatric disorders.

Structural brain connectivity correlates with outcome in mild traumatic brain injury

We investigated the topology of structural brain connectivity networks and its association to outcome following mild traumatic brain injury, a major cause of permanent disability. Eighty-five patients with mild traumatic brain injury underwent MRI twice, about three weeks and eight months after injury, and 30 age-matched orthopedic trauma control subjects were scanned. Outcome was assessed with Extended Glasgow Outcome Scale on average eight months after injury. We performed constrained spherical deconvolution based probabilistic streamlines tractography on diffusion MRI data and parcellated cortical and subcortical gray matter into 84 regions based on T1-weighted data to reconstruct structural brain connectivity networks weighted by the number of streamlines. Graph theoretical methods were employed to measure network properties in both patients and controls, and correlations between these properties and outcome were calculated. We found no global differences in the network properties between patients with mild traumatic brain injury and orthopedic control subjects at either stage. However, we found significantly increased betweenness centrality of the right pars opercularis in the chronic stage compared to control subjects. Furthermore, both global and local network properties correlated significantly with outcome. Higher normalized global efficiency, degree, and strength as well as lower small-worldness were associated with better outcome. Correlations between the outcome and the local network properties were the most prominent in the left putamen and the left postcentral gyrus. Our results indicate that both global and local network properties provide valuable information about the outcome already in the acute/subacute stage, and therefore, are promising biomarkers for prognostic purposes in mild traumatic brain injury.

Distinguish bipolar and major depressive disorder in adolescents based on multimodal neuroimaging: Results from the Adolescent Brain Cognitive Development study®

Background

Major depressive disorder and bipolar disorder in adolescents are prevalent and are associated with cognitive impairment, executive dysfunction, and increased mortality. Early intervention in the initial stages of major depressive disorder and bipolar disorder can significantly improve personal health.

Methods

We collected 309 samples from the Adolescent Brain Cognitive Development study, including 116 adolescents with bipolar disorder, 64 adolescents with major depressive disorder, and 129 healthy adolescents, and employed a support vector machine to develop classification models for identification. We developed a multimodal model, which combined functional connectivity of resting-state functional magnetic resonance imaging and four anatomical measures of structural magnetic resonance imaging (cortical thickness, area, volume, and sulcal depth). We measured the performances of both multimodal and single modality classifiers.

Results

The multimodal classifiers showed outstanding performance compared with all five single modalities, and they are 100% for major depressive disorder versus healthy controls, 100% for bipolar disorder versus healthy control, 98.5% (95% CI: 95.4–100%) for major depressive disorder versus bipolar disorder, 100% for major depressive disorder versus depressed bipolar disorder and the leave-one-site-out analysis results are 77.4%, 63.3%, 79.4%, and 81.7%, separately.

Conclusions

The study shows that multimodal classifiers show high classification performances. Moreover, cuneus may be a potential biomarker to differentiate major depressive disorder, bipolar disorder, and healthy adolescents. Overall, this study can form multimodal diagnostic prediction workflows for clinically feasible to make more precise diagnose at the early stage and potentially reduce loss of personal pain and public society.

Neural biomarker of functional disability in major depressive disorder: A structural neuroimaging study

BACKGROUND

Most patients with the major depressive disorder (MDD) have varying degrees of impaired social functioning, and functional improvement often lags behind symptomatic improvement. However, it is still unclear if certain neurobiological factors underlie the deficits of social function in MDD. The aim of this study was to investigate the biomarkers of social function in MDD using structural magnetic resonance imaging (MRI).

METHODS

3T anatomical MRI was obtained from 272 subjects including 46 high-functioning (high-SF, Sheehan Disability Scale (SDS) rating < 18) and 63 low-functioning (low-SF, SDS score ≥ 18) patients with MDD and 163 healthy controls (HC). Voxel-based morphometry (VBM) was employed to locate brain regions with grey matter (GM) volume differences in relation to social function in MDD. Regions showing GM differences in relation to social function at baseline were followed up longitudinally in a subset of 38 patients scanned after 12-week treatment.

RESULTS

Volume of right parahippocampal gyrus (rPHG) was significantly reduced in low-SF patients with MDD when compared to high-SF ones (FDR-corrected p < 0.05). Over 12 weeks of follow-up, though SF improved overall, the high and low-SF subgroups continued to differ in their SF, but had no progressive changes in PHG volume.

LIMITATIONS

Limited functional assessment, high drop-out rate and median-based grouping method.

CONCLUSIONS

Greater GM volume (GMV) of the rPHG may mark better social function in patients with MDD.

Subthreshold depressive symptoms relate to cuneus structure: Thickness asymmetry and sex differences

Despite the prominence of frontolimbic regions in depression research, recent studies also implicate posterior brain regions, including the cuneus. The current study examined the relationship between depressive symptoms and asymmetry in cuneal cortical thickness in healthy adults between the ages of 18 and 81 with primarily subthreshold levels of depressive symptoms. An asymmetry index was calculated for cortical thickness in the cuneus [(left - right) × 100/(left + right)], and regression analyses were conducted with total scores on the Center for Epidemiologic Studies Depression Scale predicting this asymmetry index, controlling for age and sex. Higher depressive symptoms were associated with a left > right asymmetry in cuneal cortical thickness, reflecting greater cortical thickness in the left hemisphere compared to right hemisphere. Follow-up analyses examining CES-D subscales showed significant effects for somatic symptoms of depression, but not negative affect or anhedonia. Analyses stratified by sex yielded significant effects in men but not in women. Results of this preliminary study further support the cuneus' role in depression and highlight the importance of examining symptom dimensions and sex differences in the neurobiology of depression.

Heterogeneous alterations in thalamic subfields in major depression disorder

BACKGROUND

It is well known that the thalamus is not a unitary and homogeneous entity but a complex and highly connected archeocortical structure. Although many neuroimaging studies have reported alterations in the thalamus in major depressive disorder (MDD), the structural alterations in thalamic subfields remain unclear. This study aimed to investigate changes in gray matter volume (GMV) in thalamic subfields in MDD patients.

METHODS

The present study included structural images of 848 MDD patients and 794 age-matched normal controls (NC) from 17 study sites of the REST-meta-MDD consortium. We performed voxel-based morphometric analyses to calculate the GMV in the entire thalamus and its subfields using three different automated anatomical labeling atlases and subsequently compared the differences between first-episode drug-naïve major depressive disorder (FEDN), recurrent major depressive disorder (RMDD), and NC groups. We also evaluated the relationships between thalamic GMV and clinical symptoms in MDD patients.

RESULTS

Compared to NC, the FEDN patients showed increased GMV in thalamic subfields but not in the entire thalamus, while RMDD patients showed no significant alterations in GMV in the entire thalamus and its subfields. Moreover, the mean GMV in the right anterior thalamus and left anteroventral thalamus in RMDD patients were mildly positively correlated with the Hamilton Anxiety Rating Scale scores.

LIMITATIONS

The main limitations are a single-modal analysis based on T1-weighted MR images and a cross-sectional design.

CONCLUSIONS

Our findings suggest that FEDN and RMDD patients show heterogeneous alterations across thalamic subfields, which may help us understand the pathophysiological mechanisms of MDD.

Grey matter volume abnormalities in the first depressive episode of medication-naïve adult individuals: a systematic review of voxel based morphometric studies

BACKGROUND

To identify the reliable and consistent grey matter volume (GMV) abnormalities associated with major depressive disorder (MDD), we excluded the influence of confounding clinical characteristics, comorbidities and brain degeneration on brain morphological abnormalities by inclusion of non-comorbid and non-geriatric drug-naïve MDD individuals experiencing first episode depressive.

METHODS

The PubMed, Scopus, Web of Science, Science Direct and Google scholar databases were searched for papers published in English up to April 2020.

RESULTS

A total of 21 voxel based morphometric (VBM) studies comparing 845 individuals in the first depressive episode and medication-naïve with 940 healthy control subjects were included. The results showed a grey matter volumes reductions in the orbitofrontal cortex (OFC), prefrontal cortex (PFC), frontal and temporal gyri, temporal pole, insular lobe, thalamus, basal ganglia, cerebellum, hippocampus, cingulate cortex, and amygdala. In addition, increased grey matter volumes in the postcentral gyrus, superior frontal gyrus, insula, basal ganglia, thalamus, amygdala, cuneus, and precuneus differentiated the first depressive episode in medication-naïve individuals from healthy subjects.

CONCLUSION

The present systematic review provided additional support for the involvement of grey matter structural abnormalities in limbic-cortical circuits as possibly specific structural abnormalities in the early stage of MDD.Key pointsDistinct brain regions in MDD patients might be associated with the early stages of illness, and thus it is critical to study the causal relationship between brain structures and the onset of the disease to improve the evaluation in clinic.Grey matter alterations in the fronto-limbic networks in the first episode, medication-naïve MDD might suggest that these abnormalities may play an important role in the neuropathophysiology of MDD at its onset.First episode, medically naïve depressive patients show grey matter volume alterations in brain regions mainly associated with emotion regulation including parietal-temporal regions, PFC, insular lobe, thalamus, basal ganglia, cerebellum and limbic structures that may be specific changes in early stage of MDD.Genotype-diagnosis interaction effects on brain morphology in the cortico-limbic-striatal circuits, including the PFC, amygdala, hippocampus and striatum that might be implicated in the dysfunctional regulation of emotion in first-episode MDD patients.Future longitudinal and prospective studies should be conducted to identify the core structural brain changes in people at-risk for MDD and explore the association of their brain volumes with symptom onset.

Alterations in the Occipital Cortex of Drug-Naïve Adults With Major Depressive Disorder: A Surface-Based Analysis of Surface Area and Cortical Thickness

OBJECTIVE

Advances in surface-based morphometric methods have allowed researchers to separate cortical volume into cortical thickness (CTh) and surface area (SA). Although CTh alterations in major depressive disorder (MDD) have been observed in numerous studies, few studies have described significant SA alterations. Our study aimed to measure patients' SAs and to compare it with their CTh to examine whether SA exhibits alteration patterns that differ from those of CTh in drug-naïve patients with MDD.

METHODS

A total of 71 drug-naïve MDD patients and 111 healthy controls underwent structural magnetic resonance imaging, and SA and CTh were analyzed between the groups.

RESULTS

We found a smaller SA in the left superior occipital gyrus (L-SOG) in drug-naïve patients with MDD. In the CTh analysis, the bilateral fusiform gyrus, left middle occipital gyrus, left temporal superior gyrus, and right posterior cingulate showed thinner cortices in patients with MDD, while the CTh of the bilateral SOG, right straight gyrus, right posterior cingulate, and left lingual gyrus were increased.

CONCLUSION

Compared with the bilateral occipito-temporal changes in CTh, SA alterations in patients with MDD were confined to the L-SOG. These findings may improve our understanding of the neurobiological mechanisms of SA alteration in relation to MDD.

Neuroinflammation in Major Depressive Disorder: A Review of PET Imaging Studies Examining the 18-kDa Translocator Protein

BACKGROUND

Major Depressive Disorder (MDD) is a severe psychiatric disorder whose pathological mechanisms are largely unknown. In the field of immuno-psychiatry, several evidences suggested a prominent role of inflammation in MDD not only in peripheral immune system but also in the brain. To date, brain inflammation is traceable in vivo with Positron Emission Tomography (PET), through the quantification of the expression of 18-kda Translocator Protein (TSPO) by active microglia. In this context, this review aimed to summarize the results of all in vivo PET imaging studies that evaluated microglia activation in MDD.

METHODS

A bibliographic search in PubMed up to June 2020 was performed. A total of 9 studies that used first and second generation TSPO radiotracers met our inclusion criteria.

RESULTS

Overall the results suggested the presence of TSPO upregulation in MDD, especially in anterior cingulate cortex, prefrontal cortex, hippocampal formation and insula. Notably, from a therapeutic point of view, results suggested that the symptoms amelioration, caused by both antidepressant medication and cognitive behavioural therapy, may be accompanied by reduced inflammatory status in the brain. Finally, a positive effect of the anti-inflammatory treatment with a cyclooxygenase inhibitor has also been observed.

LIMITATIONS

The heterogeneity across the studies in experimental designs, sample selection and methods limited the studies comparison.

CONCLUSIONS

These findings supported the presence of neuroinflammation in MDD, suggesting that microgliosis may be an important pathophysiological mechanism that merits further investigation as a potential target for novel treatment strategies.

Sleep disturbances are associated with cortical and subcortical atrophy in alcohol use disorder

Sleep disturbances are prominent in patients with alcohol use disorder (AUD) and predict relapse. So far, the mechanisms underlying sleep disruptions in AUD are poorly understood. Because sleep-related regions vastly overlap with regions, where patients with AUD showed pronounced grey matter (GM) reduction; we hypothesized that GM structure could contribute to sleep disturbances associated with chronic alcohol use. We combined sleep EEG recording and high-resolution structural brain imaging to examine the GM-sleep associations in 36 AUD vs. 26 healthy controls (HC). The patterns of GM-sleep associations differed for N3 vs. REM sleep and for AUD vs. HC. For cortical thickness (CT), CT-sleep associations were significant in AUD but not in HC and were lateralized such that lower CT in right hemisphere was associated with shorter N3, whereas in left hemisphere was associated with shorter REM sleep. For the GM density (GMD), we observed a more extensive positive GMD-N3 association in AUD (right orbitofrontal cortex, cerebellum, dorsal cingulate and occipital cortex) than in HC (right orbitofrontal cortex), and the GMD-REM association was positive in AUD (midline, motor and paralimbic regions) whereas negative in HC (the left supramarginal gyrus). GM structure mediated the effect of chronic alcohol use on the duration of N3 and the age by alcohol effect on REM sleep. Our findings provide evidence that sleep disturbances in AUD were associated with GM reductions. Targeting sleep-related regions might improve sleep in AUD and enhance sleep-induced benefits in cognition and emotional regulation for recovery.

Decreased cortical thickness of left premotor cortex as a treatment predictor in major depressive disorder

This study aimed to examine the cerebral cortex characteristics (thickness, surface area, and curvature) in patients with major depressive disorder (MDD), and explore whether these cortex characteristics are predictors for the antidepressant therapeutic effect. 105 patients with MDD and 49 healthy controls (HCs) were recruited. Both groups were given magnetic resonance image (MRI) scans at baseline period, and then the cerebral cortex characteristics (thickness, surface area, and curvature) were calculated using the DPABISurf software. The Hamilton Depression Scale-24 (HAMD-24) reductive rate was used to measure antidepressant therapeutic effect and Snaith Hamilton Rating Scale (SHAPS) reduction was performed to assess the change of anhedonia after treatment of 8 weeks. Correlation analysis was performed to identify the relationship between cortex characteristics and antidepressant therapeutic effect in patients with MDD. There were no significant differences in the cortical curvature and surface area between MDD and HC groups, while significant decreases were found in the cortical thickness of inferior frontal cortex (IFC), premotor cortex (PMC), orbital and medial prefrontal cortex (OMPFC) in the left hemisphere of MDD group, comparing with HC group (P < 0.05 for all, corrected by threshold-free cluster enhancement). In MDD group, the cortical thickness of left PMC had significant positive correlations with 8-week HAMD-24 reduction (r = 0.228, P = 0.020) and HAMD-24 reductive rate (r = 0.193, P = 0.048); and a negative correlation with the 8-week SHAPS reduction (r = -0.240, P = 0.018). Decreased cortical thickness in left PMC may be a predictor of therapeutic effect in MDD. Determining the cortical thickness of this region before treatment can provide certain reference value for clinical antidepressant treatment.

Orbitofrontal and Cingulate Thickness Asymmetry Associated with Depressive Symptom Dimensions

Both clinical depression and subthreshold depressive symptoms have been associated with alterations in cortical thickness. Studies have yielded conflicting results regarding whether cortical thinning or cortical thickening best characterize the depressive state. Also unclear is whether cortical thickness differences are lateralized. This study examined the relationship between depressive symptom dimensions and cortical thickness asymmetry in cingulate and orbitofrontal regions. Fifty-four community-dwelling adults between the ages of 18 and 81 years received a 3-Tesla magnetic resonance imaging scan and completed the Center for Epidemiologic Studies Depression Scale (CES-D). Cortical thickness values were extracted for the rostral anterior cingulate, caudal anterior cingulate, posterior cingulate, isthmus cingulate, and orbitofrontal cortex. An asymmetry index was calculated for each region. Data were analyzed using separate general linear models for each region, in which the CES-D somatic symptoms, negative affect, and anhedonia subscale scores predicted the asymmetry indices, controlling for age and sex. Higher scores on the anhedonia subscale were associated with right-sided asymmetry in orbitofrontal thickness, whereas higher somatic symptom subscale scores predicted greater left-sided asymmetry in posterior cingulate thickness. Follow-up analyses showed the orbitofrontal effect was specific to the medial, not the lateral, orbitofrontal cortex. These results suggest asymmetries in cortical thickness are apparent at even subthreshold levels of depressive symptoms, as all but five participants were below the CES-D cutoff for clinical depression, and that the relationship varies for different symptom dimensions of depression. Understanding brain asymmetries across the range of depressive symptom severity is important for informing targeted depression treatment.

The interaction effect of early trauma exposure and a diagnosis of panic disorder on cortical thickness

BACKGROUND

Early trauma (ET) is a risk factor for adult psychiatric disorders. ET exposure is known to cause structural brain alterations, particularly in the fronto-temporo-limbic circuitry. ET-related effects on brain development may differ based on individual characteristics and cause different psychiatric outcomes. We investigated the interaction effect of ET exposure and panic disorder (PD) on cortical thickness.

METHODS

Sixty-six participants with PD and 66 healthy controls were enrolled. High-resolution T1-weighted images were acquired, and a whole-brain vertex-based analysis was performed to estimate cortical thickness. The Early Trauma Inventory Self Report-Short Form, Anxiety Sensitivity Inventory-Revised, Panic Disorder Severity Scale, Beck Depression Inventory-II, and Beck Anxiety Inventory were administered.

RESULTS

There was a significant interaction between ET exposure and PD on the mean cortical thickness in the bilateral insula and right pars triangularis. An exploratory correlational analysis revealed a positive correlation between the mean cortical thickness in the left insula and severity of anxiety sensitivity to cardiovascular symptoms in participants with PD.

LIMITATIONS

Our findings may be affected by recall bias because this study is limited by its retrospective cross-sectional design.

CONCLUSIONS

Our findings suggest that ET exposure may affect brain structures differently based on a diagnosis of PD. Furthermore, individual variations in brain alterations after ET may confer trait vulnerability that triggers the development of PD. Future longitudinal studies are warranted to elucidate the neurobiological mechanisms underlying ET and psychiatric outcomes.

Effects of polygenic risk for major mental disorders and cross-disorder on cortical complexity

BACKGROUND

MRI-derived cortical folding measures are an indicator of largely genetically driven early developmental processes. However, the effects of genetic risk for major mental disorders on early brain development are not well understood.

METHODS

We extracted cortical complexity values from structural MRI data of 580 healthy participants using the CAT12 toolbox. Polygenic risk scores (PRS) for schizophrenia, bipolar disorder, major depression, and cross-disorder (incorporating cumulative genetic risk for depression, schizophrenia, bipolar disorder, autism spectrum disorder, and attention-deficit hyperactivity disorder) were computed and used in separate general linear models with cortical complexity as the regressand. In brain regions that showed a significant association between polygenic risk for mental disorders and cortical complexity, volume of interest (VOI)/region of interest (ROI) analyses were conducted to investigate additional changes in their volume and cortical thickness.

RESULTS

The PRS for depression was associated with cortical complexity in the right orbitofrontal cortex (right hemisphere: p = 0.006). A subsequent VOI/ROI analysis showed no association between polygenic risk for depression and either grey matter volume or cortical thickness. We found no associations between cortical complexity and polygenic risk for either schizophrenia, bipolar disorder or psychiatric cross-disorder when correcting for multiple testing.

CONCLUSIONS

Changes in cortical complexity associated with polygenic risk for depression might facilitate well-established volume changes in orbitofrontal cortices in depression. Despite the absence of psychopathology, changed cortical complexity that parallels polygenic risk for depression might also change reward systems, which are also structurally affected in patients with depressive syndrome.

Brain Structure and Subclinical Symptoms: A Dimensional Perspective of Psychopathology in the Depression and Anxiety Spectrum

Human psychopathology is the result of complex and subtle neurobiological alterations. Categorial DSM or ICD diagnoses do not allow a biologically founded and differentiated description of these diverse processes across a spectrum or continuum, emphasising the need for a scientific and clinical paradigm shift towards a dimensional psychiatric nosology. The subclinical part of the spectrum is, however, of special interest for early detection of mental disorders. We review the current evidence of brain structural correlates (grey matter volume, cortical thickness, and gyrification) in non-clinical (psychiatrically healthy) subjects with minor depressive and anxiety symptoms. We identified 16 studies in the depressive spectrum and 20 studies in the anxiety spectrum. These studies show effects associated with subclinical symptoms in the hippocampus, anterior cingulate cortex, and anterior insula similar to major depression and changes in amygdala similar to anxiety disorders. Precuneus and temporal areas as parts of the default mode network were affected specifically in the subclinical studies. We derive several methodical considerations crucial to investigations of brain structural correlates of minor psycho(patho)logical symptoms in healthy participants. And we discuss neurobiological overlaps with findings in patients as well as distinct findings, e.g. in areas involved in the default mode network. These results might lead to more insight into the early pathogenesis of clinical significant depression or anxiety and need to be enhanced by multi-centre and longitudinal studies.