Resting-state functional connectivity of the anterior cingulate cortex in young adults depressed patients with and without suicidal behavior

Increased functional connectivity within the salience network in patients with insomnia

BACKGROUND

Insomnia is a common sleep disorder with significant negative impacts on emotional states; however, the underlying mechanism of insomnia with comorbid emotional dysregulation remains largely unknown. The salience network (SN) plays an important role in both sleep and emotional regulation. The study aimed to explore the specific alterations in functional connectivity (FC) within the SN in insomnia patients.

METHODS

A total of 30 eligible patients with insomnia disorder (ID group) and 30 healthy controls (HC group) underwent resting-state functional magnetic resonance imaging (fMRI) scanning and psychometric assessments. Differences in FC within the SN were examined using seed-based region-to-region connectivity analysis.

RESULTS

Compared with healthy controls, patients with insomnia showed increased FC within the SN, mainly between the anterior cingulate cortex (ACC) and right superior frontal gyrus (SFG), the right SFG and right supramarginal gyrus (SMG), and between the right insular (INS) and left SMG (P<0.05). Additionally, significant correlations were observed between increased FC and the Hamilton Depression Rating Scale (HAMD), Pittsburgh Sleep Quality Index (PSQI), and Hamilton Anxiety Rating Scale (HAMA) scores (P<0.05, after Bonferroni correction).

CONCLUSIONS

These results suggest that increased FC within the SN may be related to poor sleep quality and negative emotions, highlighting the importance of the SN in the pathophysiological mechanisms of insomnia with comorbid emotional dysregulation.

Functional connectivity and network analysis in adolescents with major depressive disorder showing suicidal behavior

BACKGROUND

This study aimed to gather a homogeneous sample of adolescent patients to analyze the differences in functional connectivity and brain network parameters between suicidal and non-suicidal major depressive disorder (MDD) patients using a data-driven whole-brain approach.

METHODS

Patients recruited at the psychiatry department of Korea University Guro Hospital from November 2014 to March 2020 were diagnosed with MDD, were 13-18 years old, had IQ scores >80, had no family history of psychotic or personality disorders, had no smoking or alcohol consumption history, and were drug-naïve to psychotropic medication. Depressive symptoms were assessed using the Hamilton Depression Rating Scale and the Children's Depression Inventory. Structural and functional MRI scans were conducted and analyzed using the CONN toolbox.

RESULTS

Of 74 enrolled patients, 62 were analyzed. Regions of interest (ROIs) showing higher betweenness centrality in non-suicidal patients were the left superior temporal gyrus and left supramarginal gyrus. ROIs showing higher betweenness centrality in suicidal patients were the right hippocampus, left intracalcarine cortex, right inferior temporal gyrus, and the lateral visual network. Suicidal patients also showed different resting state functional connectivity profiles from non-suicidal patients.

LIMITATIONS

Small sample size.

CONCLUSION

Suicidal patients may overthink and overvalue future risks while having a more negatively biased autobiographical memory. Social cognition and the ability to overcome egocentricity bias seem to weaken. Such features can disrupt cognitive recovery and resilience, leading to more suicidal behaviors. Therefore, increased suicidality is not acquired, but is an innate trait.

Resting-State Functional Connectivity of the Anterior Cingulate Cortex Among Persons With Mood Disorders and Suicidal Behaviors

OBJECTIVE

To assess whether anterior cingulate cortex (ACC) abnormalities contribute to suicide risk in major depressive disorder and bipolar disorder, the investigators compared resting-state functional connectivity (rsFC) of ACC subdivisions between individuals with major depressive or bipolar disorder with and without a lifetime history of suicidal behavior.

METHODS

Forty-two inpatients with and 26 inpatients without a history of suicidal behavior (SB+ and SB-, respectively) associated with major depressive or bipolar disorder and 40 healthy control (HC) participants underwent rsFC neuroimaging. RsFC of the subgenual, perigenual, rostral, dorsal, and caudal subdivisions of the ACC was calculated. Possible confounders, such as psychosis and severity of depression, were controlled for, seed-to-voxel and post hoc region of interest (ROI)-to-ROI analyses were performed, and the accuracy of rsFC in classifying suicidal behavior was studied.

RESULTS

Compared with individuals in the SB- and HC groups, patients in the SB+ group had higher rsFC between the left rostral and right dorsal ACC seeds and visual cortex clusters. Conversely, rsFC between the left rostral and right dorsal ACC seeds and cingulate and frontal clusters was lower in the SB+ group than in the HC group. Left rostral ACC to left Brodmann's area 18 connectivity showed up to 75% discriminative accuracy in distinguishing SB+ from SB- patients.

CONCLUSIONS

A history of suicidal behavior among individuals with major depressive disorder or bipolar disorder was associated with altered rsFC of the rostral and caudal ACC, regions involved in conflict detection and error monitoring. Replication of these findings is needed to further explore the involvement of the ACC in the neurobiology of suicidal behavior and suicidal ideation.

A randomized controlled trial of desvenlafaxine-induced structural brain changes in the treatment of persistent depressive disorder

The anatomical changes that antidepressant medications induce in the brain and through which they exert their therapeutic effects remain largely unknown. We randomized 61 patients with Persistent Depressive Disorder (PDD) to receive either desvenlafaxine or placebo in a 12-week trial and acquired anatomical MRI scans in 42 of those patients at baseline before randomization and immediately at the end of the trial. We also acquired MRIs once in 39 age- and sex-matched healthy controls. We assessed whether the serotonin-norepinephrine reuptake inhibitor, desvenlafaxine, differentially changed cortical thickness during the trial compared with placebo. Patients relative to controls at baseline had thinner cortices across the brain. Although baseline thickness was not associated with symptom severity, thicker baseline cortices predicted greater reduction in symptom severity in those treated with desvenlafaxine but not placebo. We did not detect significant treatment-by-time effects on cortical thickness. These findings suggest that baseline thickness may serve as predictive biomarkers for treatment response to desvenlafaxine. The absence of treatment-by-time effects may be attributable either to use of insufficient desvenlafaxine dosing, a lack of desvenlafaxine efficacy in treating PDD, or the short trial duration.

Structural and functional brain correlates of suicidal ideation and behaviors in depression: A scoping review of MRI studies

Identifying and integrating the neural correlates of suicidal ideation and behaviors is crucial to expand the knowledge and develop targeted strategies to prevent suicide. This review aimed to describe the neural correlates of suicidal ideation, behavior and the transition between them, using different magnetic resonance imaging (MRI) modalities, providing an up-to-date overview of the literature. To be included, the observational, experimental, or quasi-experimental studies must include adult patients currently diagnosed with major depressive disorder and investigate the neural correlates of suicidal ideation, behavior and/or the transition using MRI. The searches were conducted on PubMed, ISI Web of Knowledge and Scopus. Fifty articles were included in this review: 22 on suicidal ideation, 26 on suicide behaviors and two on the transition between them. The qualitative analysis of the included studies suggested alterations in the frontal, limbic and temporal lobes in suicidal ideation associated with deficits in emotional processing and regulation, and in the frontal, limbic, parietal lobes, and basal ganglia in suicide behaviors associated with impairments in decision-making. Gaps in the literature and methodological concerns were identified and might be addressed in future studies.

Resting-state neural mechanisms of capability for suicide and their interaction with pain - A CAN-BIND-05 Study

BACKGROUND

Suicidal ideation is highly prevalent in Major Depressive Disorder (MDD). However, the factors determining who will transition from ideation to attempt are not established. Emerging research points to suicide capability (SC), which reflects fearlessness of death and increased pain tolerance, as a construct mediating this transition. This Canadian Biomarker Integration Network in Depression study (CANBIND-5) aimed to identify the neural basis of SC and its interaction with pain as a marker of suicide attempt.

METHODS

MDD patients (n = 20) with suicide risk and healthy controls (n = 21) completed a self-report SC scale and a cold pressor task measuring pain threshold, tolerance, endurance, and intensity at threshold and tolerance. All participants underwent a resting-state brain scan and functional connectivity was examined for 4 regions: anterior insula (aIC), posterior insula (pIC), anterior mid-cingulate cortex (aMCC) and subgenual anterior cingulate cortex (sgACC).

RESULTS

In MDD, SC correlated positively with pain endurance and negatively with threshold intensity. Furthermore, SC correlated with the connectivity of aIC to the supramarginal gyrus, pIC to the paracingulate gyrus, aMCC to the paracingulate gyrus, and sgACC to the dorsolateral prefrontal cortex. These correlations were stronger in MDD compared to controls. Only threshold intensity mediated the correlation between SC and connectivity strength.

LIMITATIONS

Resting-state scans provided an indirect assessment of SC and the pain network.

CONCLUSIONS

These findings highlight point to a neural network underlying SC that is associated with pain processing. This supports the potential clinical utility of pain response measurement as a method to investigate markers of suicide risk.

Neuroimaging alterations of the suicidal brain and its relevance to practice: an updated review of MRI studies

Suicide is a leading cause of death in the United States. Historically, scientific inquiry has focused on psychological theory. However, more recent studies have started to shed light on complex biosignatures using MRI techniques, including task-based and resting-state functional MRI, brain morphometry, and diffusion tensor imaging. Here, we review recent research across these modalities, with a focus on participants with depression and Suicidal Thoughts and Behavior (STB). A PubMed search identified 149 articles specific to our population of study, and this was further refined to rule out more diffuse pathologies such as psychotic disorders and organic brain injury and illness. This left 69 articles which are reviewed in the current study. The collated articles reviewed point to a complex impairment showing atypical functional activation in areas associated with perception of reward, social/affective stimuli, top-down control, and reward-based learning. This is broadly supported by the atypical morphometric and diffusion-weighted alterations and, most significantly, in the network-based resting-state functional connectivity data that extrapolates network functions from well validated psychological paradigms using functional MRI analysis. We see an emerging picture of cognitive dysfunction evident in task-based and resting state fMRI and network neuroscience studies, likely preceded by structural changes best demonstrated in morphometric and diffusion-weighted studies. We propose a clinically-oriented chronology of the diathesis-stress model of suicide and link other areas of research that may be useful to the practicing clinician, while helping to advance the translational study of the neurobiology of suicide.

The characterization of static and dynamic brain functional networks in suicide attempters with major depressive disorder and its relation to psychological pain

Psychological pain is a robust predictor of suicide attempts in patients with major depressive disorder (MDD). However, whether suicide and psychological pain share a common neural basis remains unclear. Patients with MDD (n = 64) and healthy controls (HC) (n = 35) were recruited and patients were allocated to two groups: those with a history of suicide attempts (MDD-SA) (n = 25) and those without such a history (MDD-NSA) (n = 39). All participants completed the measurements and underwent functional magnetic resonance imaging to investigate the resting-state static and dynamic brain functional networks in default mode (DMN), central executive (CEN), salience (SN), and basal ganglia (BGN) networks. The MDD-SA group scored higher in pain avoidance than the MDD-NSA and HC groups. Functional connectivity within the dorsal DMN in the MDD-SA group was greater than that in the MDD-NSA and HC groups, and was significantly correlated with pain avoidance and suicide attempts. Dynamic functional connectivity analysis revealed that the proportion of State I in the fraction windows in the MDD-SA group was higher than those in the MDD-NSA and HC groups. Therefore, the increased functional connectivity within the dorsal DMN and segregation of networks may represent potential biological markers for suicide attempts related to psychological pain processing.

Identification of suicidality in patients with major depressive disorder via dynamic functional network connectivity signatures and machine learning

Major depressive disorder (MDD) is a severe brain disease associated with a significant risk of suicide. Identification of suicidality is sometimes life-saving for MDD patients. We aimed to explore the use of dynamic functional network connectivity (dFNC) for suicidality detection in MDD patients. A total of 173 MDD patients, including 48 without suicide risk (NS), 74 with suicide ideation (SI), and 51 having attempted suicide (SA), participated in the present study. Thirty-eight healthy controls were also recruited for comparison. A sliding window approach was used to derive the dFNC, and the K-means clustering method was used to cluster the windowed dFNC. A linear support vector machine was used for classification, and leave-one-out cross-validation was performed for validation. Other machine learning methods were also used for comparison. MDD patients had widespread hypoconnectivity in both the strongly connected states (states 2 and 5) and the weakly connected state (state 4), while the dysfunctional connectivity within the weakly connected state (state 4) was mainly driven by suicidal attempts. Furthermore, dFNC matrices, especially the weakly connected state, could be used to distinguish MDD from healthy controls (area under curve [AUC] = 82), and even to identify suicidality in MDD patients (AUC = 78 for NS vs. SI, AUC = 88 for NS vs. SA, and AUC = 74 for SA vs. SI), with vision-related and default-related inter-network connectivity serving as important features. Thus, the dFNC abnormalities observed in this study might further improve our understanding of the neural substrates of suicidality in MDD patients.

Multimodal Neural Evidence on the Corticostriatal Underpinning of Suicidality in Late-Life Depression

BACKGROUND

Suicidality involves thoughts (ideations and plans) and actions related to self-inflicted death. To improve management and prevention of suicidality, it is essential to understand the key neural mechanisms underlying suicidal thoughts and actions. Following empirically informed neural framework, we hypothesized that suicidal thoughts would be primarily characterized by alterations in the default mode network indicating disrupted self-related processing, whereas suicidal actions would be characterized by changes in the lateral prefrontal corticostriatal circuitries implicating compromised action control.

METHODS

We analyzed the gray matter volume and resting-state functional connectivity of 113 individuals with late-life depression, including 45 nonsuicidal patients, 33 with suicidal thoughts but no action, and 35 with past suicidal action. Between-group analyses revealed key neural features associated with suicidality. The functional directionality of the identified resting-state functional connectivity was examined using dynamic causal modeling to further elucidate its mechanistic nature. Post hoc classification analysis examined the contribution of the neural measures to suicide classification.

RESULTS

As expected, reduced gray matter volumes in the default mode network and lateral prefrontal regions characterized patients with suicidal thoughts and those with past suicidal actions compared with nonsuicidal patients. Furthermore, region-of-interest analyses revealed that the directionality and strength of the ventrolateral prefrontal cortex-caudate resting-state functional connectivity were related to suicidal thoughts and actions. The neural features significantly improved classification of suicidal thoughts and actions over that based on clinical and suicide questionnaire variables.

CONCLUSIONS

Gray matter reductions in the default mode network and lateral prefrontal regions and the ventrolateral prefrontal cortex-caudate connectivity alterations characterized suicidal thoughts and actions in patients with late-life depression.

Pain avoidance and functional connectivity between insula and amygdala identifies suicidal attempters in patients with major depressive disorder using machine learning

Pain avoidance can effectively classify suicide attempters from non-attempters among patients with major depressive disorder (MDD). However, the neural circuits underlying pain processing in suicide attempters have not been described comprehensively. In Study 1, we recruited MDD patients with a history of suicide attempts (MDD-SA), and those without (MDD-NSA) to examine the patterns of psychological pain using the latent profile analysis. Further, in Study 2, participants including the MDD-SA, MDD-NSA, and healthy controls underwent resting-state functional magnetic resonance imaging. We used machine learning that included features of gray matter volume (GMV), the functional connectivity (FC) brain patterns of the region of interest, and behavioral data to identify suicide attempters. The results identified three latent classes of psychological pain in MDD patients: the low pain class (18.9%), the painful feeling class (37.2%), and the pain avoidance class (43.9%). Furthermore, the proportion of suicide attempters with high pain avoidance was the highest. The accuracy of multimodality classifiers (63%-92%) was significantly higher than that of brain-only classifiers (56%-85%) and behavior-only classifiers (64%-73%). Pain avoidance ranked first in the optimal feature set of the suicide attempt classification model. The crucial brain imaging features were FC between the left amygdala and right insula, right orbitofrontal and left thalamus, left anterior cingulate cortex and left insula, right orbitofrontal, amygdala, and the GMV of right thalamus. Additionally, the optimal feature set, including pain avoidance and crucial brain patterns of psychological pain neural circuits, was provided for the identification of suicide attempters.

Correlates and predictors of the severity of suicidal ideation in adolescence: an examination of brain connectomics and psychosocial characteristics

BACKGROUND

Suicidal ideation (SI) typically emerges during adolescence but is challenging to predict. Given the potentially lethal consequences of SI, it is important to identify neurobiological and psychosocial variables explaining the severity of SI in adolescents.

METHODS

In 106 participants (59 female) recruited from the community, we assessed psychosocial characteristics and obtained resting-state fMRI data in early adolescence (baseline: aged 9-13 years). Across 250 brain regions, we assessed local graph theory-based properties of interconnectedness: local efficiency, eigenvector centrality, nodal degree, within-module z-score, and participation coefficient. Four years later (follow-up: ages 13-19 years), participants self-reported their SI severity. We used least absolute shrinkage and selection operator (LASSO) regressions to identify a linear combination of psychosocial and brain-based variables that best explain the severity of SI symptoms at follow-up. Nested-cross-validation yielded model performance statistics for all LASSO models.

RESULTS

A combination of psychosocial and brain-based variables explained subsequent severity of SI (R² = .55); the strongest was internalizing and externalizing symptom severity at follow-up. Follow-up LASSO regressions of psychosocial-only and brain-based-only variables indicated that psychosocial-only variables explained 55% of the variance in SI severity; in contrast, brain-based-only variables performed worse than the null model.

CONCLUSIONS

A linear combination of baseline and follow-up psychosocial variables best explained the severity of SI. Follow-up analyses indicated that graph theory resting-state metrics did not increase the prediction of the severity of SI in adolescents. Attending to internalizing and externalizing symptoms is important in early adolescence; resting-state connectivity properties other than local graph theory metrics might yield a stronger prediction of the severity of SI.

Understanding complex functional wiring patterns in major depressive disorder through brain functional connectome

Brain function relies on efficient communications between distinct brain systems. The pathology of major depressive disorder (MDD) damages functional brain networks, resulting in cognitive impairment. Here, we reviewed the associations between brain functional connectome changes and MDD pathogenesis. We also highlighted the utility of brain functional connectome for differentiating MDD from other similar psychiatric disorders, predicting recurrence and suicide attempts in MDD, and evaluating treatment responses. Converging evidence has now linked aberrant brain functional network organization in MDD to the dysregulation of neurotransmitter signaling and neuroplasticity, providing insights into the neurobiological mechanisms of the disease and antidepressant efficacy. Widespread connectome dysfunctions in MDD patients include multiple, large-scale brain networks as well as local disturbances in brain circuits associated with negative and positive valence systems and cognitive functions. Although the clinical utility of the brain functional connectome remains to be realized, recent findings provide further promise that research in this area may lead to improved diagnosis, treatments, and clinical outcomes of MDD.

Xiaoyaosan Exerts Antidepressant Effect by Downregulating RAGE Expression in Cingulate Gyrus of Depressive-Like Mice

Xiaoyaosan (XYS), as a classic Chinese medicine compound, has been proven to have antidepressant effect in many studies, but its mechanism has not been clarified. In our previous studies, we found that chronic stress can induce depressive-like behavior and lead to emotion-related cingulate gyrus (Cg) dysfunction, as well as the decrease of neurotrophic factors and the increase of inflammatory-related proteins. Therefore, we speculated that XYS may play an antidepressant role by regulating the inflammation-related receptor of advanced glycation protein end product (RAGE) to affect the functional connectivity (FC) signal of the Cg and improve the depressive-like behavior. In order to verify this hypothesis, we analyzed the FC and RAGE expression in the Cg of depressive-like mice induced by chronic unpredictable mild stress (CUMS) and verified it with RAGE knockout mice. At the same time, we detected the effect of XYS on the depressive-like behavior, expression of RAGE, and the FC of the Cg of mice. The results showed that the FC of the Cg of depressive-like mice induced by CUMS was weakened, and the expression of RAGE was upregulated. The antidepressant effect of XYS is similar to that of fluoxetine hydrochloride, which can significantly reduce the depressive-like behavior of mice and inhibit the expression of the RAGE protein and mRNA in the Cg, and increase the FC of the Cg in mice. In conclusion, XYS may play an antidepressant role by downregulating the expression of RAGE in the Cg of depressive-like mice induced by CUMS, thereby affecting the functional signal and improving the depressive-like behavior.

New Methods for Assessing Rapid Changes in Suicide Risk

Rapid-acting interventions for the suicide crisis have the potential to transform treatment. In addition, recent innovations in suicide research methods may similarly expand our understanding of the psychological and neurobiological correlates of suicidal thoughts and behaviors. This review discusses the limitations and challenges associated with current methods of suicide risk assessment and presents new techniques currently being developed to measure rapid changes in suicidal thoughts and behavior. These novel assessment strategies include ecological momentary assessment, digital phenotyping, cognitive and implicit bias metrics, and neuroimaging paradigms and analysis methodologies to identify neural circuits associated with suicide risk. This review is intended to both describe the current state of our ability to assess rapid changes in suicide risk as well as to explore future directions for clinical, neurobiological, and computational markers research in suicide-focused clinical trials.

Distinct effects of over-general autobiographical memory on suicidal ideation among depressed and healthy people

BACKGROUND

Childhood trauma and over-general autobiographical memory (OGM) are crucial risk factors of suicide. This study aimed to investigate whether suicidal ideation was predicted by one's childhood trauma and OGM and the mechanism of OGM underlying suicidal ideation in depression patients and healthy controls.

METHODS

A total of 180 depression patients and 176 matched healthy individuals were recruited in this study. Data were analyzed using descriptive statistics, and Pearson's correlation coefficient was obtained. Path analysis was conducted to test a meditational model. The multigroup comparison was applied to find differences between groups.

RESULTS

Significant differences were detected between depression patients and healthy controls with respect to childhood trauma, OGM, suicidal ideation, and suicidal behavior. OGM was positively correlated with both current and worst-point suicidal ideation in the depression group and significantly correlated with worst-point suicidal ideation in the healthy control group. The path model showed that childhood trauma had a direct impact on the current suicidal ideation directly, and an indirect influence through OGM and worst-point suicidal ideation. Multigroup analysis further demonstrated that OGM affected and mediated the current suicidal ideation due to childhood trauma in depression patients, whereas only worst-point suicidal ideation was affected in healthy controls.

CONCLUSIONS

The OGM mediates suicidal ideation in depression patients, but only affects the worst-point suicidal ideation in the healthy controls. As it is one of the major risk factors of suicidal ideation in depression, amelioration of OGM might be an useful method to reduce or prevent suicidal ideation in depression patients.

Chondroitin sulfate proteoglycan-5 forms perisynaptic matrix assemblies in the adult rat cortex

Composition of the brain extracellular matrix changes in time as maturation proceeds. Chondroitin sulfate proteoglycan 5 (CSPG-5), also known as neuroglycan C, has been previously associated to differentiation since it shapes neurite growth and synapse forming. Here, we show that this proteoglycan persists in the postnatal rat brain, and its expression is higher in cortical regions with plastic properties, including hippocampus and the medial prefrontal cortex at the end of the second postnatal week. Progressively accumulating after birth, CSPG-5 typically concentrates around glutamatergic and GABAergic terminals in twelve-week old rat hippocampus. CSPG-5-containing perisynaptic matrix rings often appear at the peripheral margin of perineuronal nets. Electron microscopy and analysis of synaptosomal fraction showed that CSPG-5 accumulates around, and is associated to synapses, respectively. In vitro analyses suggest that neurons, but less so astrocytes, express CSPG-5 in rat primary neocortical cultures, and CSPG-5 produced by transfected neuroblastoma cells appear at endings and contact points of neurites. In human subjects, CSPG-5 expression shifts in brain areas of the default mode network of suicide victims, which may reflect an impact in the pathogenesis of psychiatric diseases or support diagnostic power.