Journal of Psychiatry & Neuroscience最新文献

Background: Numerous neuroimaging studies investigating the neural substrates of obsessive-compulsive disorder (OCD) have yielded inconsistent findings, and growing evidence suggests that psychiatric disorders are more accurately localized to brain networks rather than discrete brain regions. We sought to identify brain network localization in OCD.

Methods: We initially examined brain locations of structural and functional alterations among patients with OCD and healthy controls using neuroimaging studies. Employing a novel technique called functional connectivity network mapping (FCNM) and large-scale human brain connectome data, we mapped these damaged brain regions to 2 brain impairment networks in OCD.

Results: We included 62 neuroimaging studies involving 2578 patients with OCD and 2502 healthy controls. For FCNM, we used data from 556 healthy adults. Among patients with OCD, the grey matter volume (GMV) and resting-state activity impairment networks encompassed a broad range of brain regions, primarily involving the default mode, sensorimotor, and limbic networks, as well as the bilateral middle frontal gyrus and bilateral middle temporal gyrus. Additionally, the GMV impairment network specifically involved bilateral inferior frontal gyrus.

Limitations: We used large-scale human brain connectome data from healthy people, rather than the samples clinically and demographically matched to the original study participants, to examine brain networks in OCD.

Conclusion: Our study integrated an FCNM method with large-scale human brain connectome data to map heterogeneous abnormal brain locations of OCD to structural and functional impairment networks. Our findings deepen our understanding of the neuropathological mechanisms of OCD from a network perspective and may inform future neuromodulation treatment.

Background: Although it has been suggested that the hippocampus and amygdala (HA) are involved in the neurobiology of obsessive-compulsive disorder (OCD), volumetric findings have been inconsistent, and little work has been undertaken on the volumetry of the heterogeneous anatomic units of HA, with their specific functions and cytoarchitecture, in OCD. We sought to explore potential sources of heterogeneity in brain volumes by performing a separate analysis for people with and without psychotropic medication use, as well as the association of subfield volumes with OCD symptom severity.

Methods: We segmented T ₁-weighted images from people with OCD and healthy controls in the OCD Brain Imaging Consortium to produce 12 hippocampal subfields and 9 amygdala subfields using Free-Surfer 6.0. We assessed between-group differences in subfield volume using a mixed-effects model adjusted for age and quadratic effects of age, sex, site, and whole HA volume. We also performed subgroup analyses to examine subfield volume in relation to comorbid anxiety and depression, medication status, and symptom severity. We corrected all analyses for multiple comparisons using the false discovery rate (FDR).

Results: We included images from 381 people with OCD and 338 healthy controls. These groups did not significantly differ in HA subfield volumes. However, medicated people with OCD had significantly smaller volumes in the hippocampal dentate gyrus (p _FDR = 0.04, d = -0.26) and molecular layer (p _FDR = 0.04, d = -0.29), and larger volumes in the lateral (p _FDR = 0.049, d = 0.23) and basal (p _FDR = 0.049, d = 0.25) amygdala subfields, than healthy controls. Unmedicated people with OCD had significantly smaller volumes in the hippocampal cornu ammonis sector 1 (p _FDR = 0.02, d = -0.28) than controls. We did not detect associations between any subfield volume and OCD severity.

Limitations: We used cross-sectional data, which limits the interpretation of our analysis.

Conclusion: Differences in HA subfields between people with OCD and healthy controls are dependent on medication status, in line with previous work on other brain volumetric alterations in OCD. This emphasizes the importance of considering psychotropic medication in neuroimaging studies of OCD.

The terminology used to describe components of social cognition lacks clarity and specificity. Recent studies have tried to reach consensus on definitions of social cognition based on expert opinion. These efforts resulted in semantically well-defined terms and distinct concepts, but it remains unclear whether these terms also align with empirical data and existing theoretical models of social cognition. In this commentary, we examine whether the proposed definitions for social cognition are supported by clinical observations and the extant knowledge base on the underlying neural substrates of these skills. In addition, we consider how the proposed definitions align with existing theoretical models of social cognition. We argue that consensus should not be based solely on expert opinion. Therefore, we propose an updated biopsychosocial model of social cognition that integrates proposed expert definitions with a theoretical model of social cognition based on empirical data: the Hierarchical Interdependent Taxonomy of Social cognition (HITS) model. The HITS model guides future research, helps to address the poor construct validity that has been revealed for several tests of social cognition, and provides a framework for the assessment of social cognition.

Background: Despite the prevalence and impact of body dysmorphic concerns on psychosocial functioning, there remains a scarcity of research examining the neurobiological and psychological correlates of these symptoms in healthy individuals. Given that previous studies on clinical body dysmorphic disorder (BDD) revealed brain structural and functional differences in limbic, frontal, and visual processing areas, as well as cognitive and emotional deficits, we sought to investigate the associations between grey matter volume (GMV), subclinical body dysmorphic symptom severity, alexithymia, and rumination.

Methods: We assessed GMV using structural magnetic resonance imaging (MRI) in a sample of healthy participants. We employed a region-of-interest (ROI) approach, including the medial orbital superior frontal gyrus (SFG), precuneus, amygdala, hippocampus, anterior cingulate cortex (ACC), and inferior occipital gyrus (IOG). We analyzed associations between ROIs and body dysmorphic symptoms, with particular emphasis on the impact of gender on these associations. We corrected p values using threshold-free cluster enhancement and established a conservative family-wise error (FWE) threshold value of 0.05.

Results: We included 219 participants. Our analysis revealed an interaction effect between body dysmorphic symptom score and gender in the right amygdala (p _FWE = 0.01), bilateral hippocampus (right p _FWE = 0.02; left p _FWE = 0.04), and right IOG (p _FWE = 0.01), reflecting a trend toward positive associations between body dysmorphic symptoms and GMV among men and negative associations among women. No significant relationships were found in the SFG, ACC, and precuneus. Women exhibited elevated levels of body dysmorphic symptoms compared with men, and body areas of concern differed between genders. Additionally, alexithymia predicted body dysmorphic symptom severity among women only.

Limitations: The specificities of structural MRI measurements and cross-sectional study designs should be taken into account when interpreting these results.

Conclusion: Our findings suggest an association between subclinical body dysmorphic symptoms and brain structure in limbic and visual areas moderated by gender. Insights into body dysmorphic symptomatology drawn from subclinical samples may offer valuable insights into predisposing factors in the etiology of BDD and may aid in developing targeted prevention strategies.

Background: Suicide risk is a major concern for patients with major depressive disorder (MDD). Neuroimaging studies have demonstrated that patients with MDD with suicidal ideation or suicide attempt (MDD-S) are accompanied by neurostructural or functional abnormalities, but there is no consensus of opinion on neural substrate alterations involved in MDD-S.

Methods: We performed a whole-brain multimodal meta-analysis of existing magnetic resonance imaging (MRI) studies to identify conjoint and separate alterations of grey matter volume (GMV) and spontaneous brain activity characteristics (regional homogeneity and amplitude of low-frequency fluctuations) between patients with MDD-S and patients with MDD without suicidal ideation or suicidal attempt (MDD-NS) via the seed-based d mapping software. We excluded studies that used other modalities, had overlapping data, or had insufficient information.

Results: Our systematic search identified 13 structural MRI studies (471 patients with MDD-S and 508 patients with MDD-NS) and 16 resting-state functional MRI studies (704 patients with MDD-S and 554 patients with MDD-NS) published up to Dec. 5, 2023. Compared with patients with MDD-NS, those with MDD-S showed increased GMV with hypoactivity in the left postcentral gyrus, decreased GMV with hypoactivity in the right inferior parietal gyri, decreased GMV with hyperactivity in the right insula, and separate GMV and functional changes within the bilateral parietal, occipital, and frontal lobes, and the left thalamus.

Limitations: We were unable to analyze the association between brain features and clinical detail because of a lack of data. Included studies showed considerable heterogeneity and publication bias.

Conclusion: These findings provide a comprehensive overview of brain morphological and spontaneous functional impairments linked to impulsivity, impaired positive reward modulation, emotional disturbances, abnormal emotional processing, and cognitive deficits in MDD-S. These results support an understanding of the relationship between neural substrates and clinical symptoms in MDD-S, and these alterations provide useful insight into pathophysiological mechanisms and intervention strategies to decrease suicide risk in MDD.

Background: Alterations in DNA, such as DNA methylation, may be key molecular events involved in the development of major depressive disorder (MDD). We sought to clarify correlations between DNA methylation profiles and symptom heterogeneity among patients with MDD.

Methods: We conducted a genome-wide DNA methylation analysis of blood samples from patients with MDD and controls, using the Infinium MethylationEPIC BeadChip.

Results: We analyzed 283 blood samples, including 141 from an initial cohort (69 patients with MDD, 72 controls) and 142 from a second validation cohort (67 patients with MDD, 75 controls). After adjustment for age, sex, and blood cell heterogeneity, DNA methylation status at 2699 CpG sites tended to differ between patients with MDD and controls in both the initial and second cohorts. Hierarchical clustering of patients based on DNA methylation status at these 2699 CpG sites revealed a significant correlation with scores for GRID-Hamilton Depression Rating Scale (GRID-HAMD) items (depressed mood, guilt, early insomnia, middle insomnia, work and activities, psychic anxiety, loss of appetite, general somatic symptoms, and total score), suggesting the feasibility of severity diagnostics based on blood DNA methylation testing. Pathway over-representation analysis revealed that genes whose DNA methylation status was correlated with epigenetic clustering were accumulated in molecular pathways involved in various cellular functions, especially nerve development. For PLEKHD1, STK10, and FOXK1, DNA methylation levels were inversely correlated with expression levels in the Clinical Proteomic Tumor Analysis Consortium database. DNA hypomethylation of PLEKHD1, STK10, and FOXK1 was correlated with higher GRID-HAMD scores in both cohorts.

Limitations: Although we performed marker exploration using 2 cohorts including 283 participants, the heterogeneity of the molecular mechanisms operating in MDD might necessitate a larger cohort for establishment of criteria with sufficient diagnostic impact.

Conclusion: These findings indicate that the DNA methylation status of specific genes may correlate with the severity of MDD symptoms, and that genome-wide DNA methylation analysis of blood samples would be useful for clarifying the DNA methylation profiles related to symptom heterogeneity.

Background: Patients with late-life depression (LLD) with suicidal ideation (SI) often have more explicit suicide plans, and suicide attempts among older adults are more highly lethal than in other age groups. Increasing evidence suggests that people with SI in depression exhibit abnormal brain network connectivity; however, the relationship between suicidal ideation in LLD and brain network dynamics is still unclear.

Methods: We recruited patients with LLD and SI (LLD-SI), patients with LLD without SI (LLD-NSI), and age-matched healthy older adults. We collected 64-channel resting state electroencephalography (EEG) recordings of all participants and used microstate analysis to explore large-scale brain network dynamics.

Results: We included 33 patients with LLD-SI, 29 patients with LLD-NSI, and 31 controls. We observed abnormal microstate parameters in the LLD-SI group, characterized by higher duration (p = 0.04), occurrence (p = 0.009), and contribution (p = 0.001) of microstate C (reflecting activity of the salience network), compared with the LLD-NSI group, as well as higher occurrence (p = 0.03) and contribution (p = 0.009) of microstate C compared with the control group. Furthermore, transition probabilities from microstate class A to D (r = -0.466, p = 0.04) and class D to A (r = -0.506, p = 0.02) (involving coupling and sequential activation of auditory and executive control network) were negatively correlated with completion time of Stroop Colour and Word Test Part C (a neuropsychological test of executive function) in the LLD-SI group.

Limitations: The sample size was relatively small, the cross-sectional nature of this study prohibited exploring the causal relationship between abnormal microstate dynamics and suicidal ideation, and we did not include medication-naive patients with first-episode LLD.

Conclusion: The study reveals altered microstate dynamics among patients with LLD-SI, compared with patients with LLD-NSI and controls. Our findings suggest that microstate dynamics could serve as potential neurobiomarkers for identifying SI in LLD.