Disrupted fronto-parietal network and default-mode network gamma interactions distinguishing suicidal ideation and suicide attempt in depression

Exploring the neurocognitive correlates of suicidal ideation in major depressive disorder: The role of frontoparietal and default mode networks

Suicidal ideation (SI) is a common symptom of major depressive disorder (MDD), often accompanied by cognitive alterations and emotional dysregulation. However, it is unclear whether cognitive dysfunction in patients with MDD is related to the presence or absence of SI and impaired connectivity within or between large-scale neurocognitive networks. Previous studies have shown that the frontoparietal network (FPN) and default mode network (DMN) are critical for cognitive control and emotional regulation. Participants were 51 MDD patients with suicidal ideation (MDDSI), 52 MDD patients without suicidal ideation (MDDNSI), and 55 healthy controls (HC). Using areas located within FPN and DMN networks as regions of interest (ROIs), we compared the cognitive performance of the three groups and the strength of the resting state functional connections (RSFC) within and between the FPN and DMN networks. Additionally, we examined the correlation between the strength of FC within the FPN and cognitive function in the SI group. Furthermore, network-based statistics (NBS) were used to correct for the strength of FPN and DMN functional connections. The study identified significant cognitive deficits in MDD patients. Reduced strength of FC was observed within the FPN and DMN networks in the SI group compared to the NSI group. In the SI group, the strength of FC within the FPN network was positively correlated with attention/vigilance. These insights underscore the critical roles of the FPN and DMN in the suicidal ideation, shedding light on the cognitively relevant neurobiological characteristics of MDDSI, providing new insights into the neural mechanisms of MDDSI. URL: https://www.chictr.org.cn/bin/project/edit?pid=131537. Registration number: ChiCTR2100049646.

Clinical, behavioral, and electrophysiological profiles along a continuum of suicide risk: evidence from an implicit association task

BACKGROUND

An urgent need exists to identify neural correlates associated with differing levels of suicide risk and develop novel, rapid-acting therapeutics to modulate activity within these neural networks.

METHODS

Electrophysiological correlates of suicide were evaluated using magnetoencephalography (MEG) in 75 adults with differing levels of suicide risk. During MEG scanning, participants completed a modified Life-Death Implicit Association Task. MEG data were source-localized in the gamma (30-58 Hz) frequency, a proxy measure of excitation-inhibition balance. Dynamic causal modeling was used to evaluate differences in connectivity estimates between risk groups. A proof-of-concept, open-label, pilot study of five high risk participants examined changes in gamma power after administration of ketamine (0.5 mg/kg), an NMDAR antagonist with rapid anti-suicide ideation effects.

RESULTS

Implicit self-associations with death were stronger in the highest suicide risk group relative to all other groups, which did not differ from each other. Higher gamma power for self-death compared to self-life associations was found in the orbitofrontal cortex for the highest risk group and the insula and posterior cingulate cortex for the lowest risk group. Connectivity estimates between these regions differentiated the highest risk group from the full sample. Implicit associations with death were not affected by ketamine, but enhanced gamma power was found for self-death associations in the left insula post-ketamine compared to baseline.

CONCLUSIONS

Differential implicit cognitive processing of life and death appears to be linked to suicide risk, highlighting the need for objective measures of suicidal states. Pharmacotherapies that modulate gamma activity, particularly in the insula, may help mitigate risk.Clinicaltrials.gov identifier: NCT02543983, NCT00397111.

Identifying unique subgroups in suicide risks among psychiatric outpatients

BACKGROUND

The presence of psychiatric disorders is widely recognized as one of the primary risk factors for suicide. A significant proportion of individuals receiving outpatient psychiatric treatment exhibit varying degrees of suicidal behaviors, which may range from mild suicidal ideations to overt suicide attempts. This study aims to elucidate the transdiagnostic symptom dimensions and associated suicidal features among psychiatric outpatients.

METHODS

The study enrolled patients who attended the psychiatry outpatient clinic at a tertiary hospital in South Korea (n = 1, 849, age range = 18-81; 61% women). A data-driven classification methodology was employed, incorporating a broad spectrum of clinical symptoms, to delineate distinctive subgroups among psychiatric outpatients exhibiting suicidality (n = 1189). A reference group of patients without suicidality (n = 660) was included for comparative purposes to ascertain cluster-specific sociodemographic, suicide-related, and psychiatric characteristics.

RESULTS

Psychiatric outpatients with suicidality (n = 1189) were subdivided into three distinctive clusters: the low-suicide risk cluster (Cluster 1), the high-suicide risk externalizing cluster (Cluster 2), and the high-suicide risk internalizing cluster (Cluster 3). Relative to the reference group (n = 660), each cluster exhibited distinct attributes pertaining to suicide-related characteristics and clinical symptoms, covering domains such as anxiety, externalizing and internalizing behaviors, and feelings of hopelessness. Cluster 1, identified as the low-suicide risk group, exhibited less frequent suicidal ideation, planning, and multiple attempts. In the high-suicide risk groups, Cluster 2 displayed pronounced externalizing symptoms, whereas Cluster 3 was primarily defined by internalizing and hopelessness symptoms. Bipolar disorders were most common in Cluster 2, while depressive disorders were predominant in Cluster 3.

DISCUSSION

Our findings suggest the possibility of differentiating psychiatric outpatients into distinct, clinically relevant subgroups predicated on their suicide risk. This research potentially paves the way for personalizing interventions and preventive strategies that address cluster-specific characteristics, thereby mitigating suicide-related mortality among psychiatric outpatients.

Explainable multimodal prediction of treatment-resistance in patients with depression leveraging brain morphometry and natural language processing

Although 20 % of patients with depression receiving treatment do not achieve remission, predicting treatment-resistant depression (TRD) remains challenging. In this study, we aimed to develop an explainable multimodal prediction model for TRD using structured electronic medical record data, brain morphometry, and natural language processing. In total, 247 patients with a new depressive episode were included. TRD-predictive models were developed based on the combination of following parameters: selected tabular dataset features, independent components-map weightings from brain T1-weighted magnetic resonance imaging (MRI), and topic probabilities from clinical notes. All models applied the extreme gradient boosting (XGBoost) algorithm via five-fold cross-validation. The model using all data sources showed the highest area under the receiver operating characteristic of 0.794, followed by models that used combined brain MRI and structured data, brain MRI and clinical notes, clinical notes and structured data, brain MRI only, structured data only, and clinical notes only (0.770, 0.762, 0.728, 0.703, 0.684, and 0.569, respectively). Classifications of TRD were driven by several predictors, such as previous exposure to antidepressants and antihypertensive medications, sensorimotor network, default mode network, and somatic symptoms. Our findings suggest that a combination of clinical data with neuroimaging and natural language processing variables improves the prediction of TRD.

Brain structural and functional signatures of multi-generational family history of suicidal behaviors in preadolescent children

Parent-child transmission of suicidal behaviors has been extensively studied, but the investigation of a three-generation family suicide risk paradigm remains limited. In this study, we aimed to explore the behavioral and brain signatures of multi-generational family history of suicidal behaviors (FHoS) in preadolescents, utilizing a longitudinal design and the dataset from Adolescent Brain and Cognitive DevelopmentSM Study (ABCD Study®), which comprised 4 years of data and includes a total of 9,653 preadolescents. Our findings revealed that multi-generational FHoS was significantly associated with an increased risk of problematic behaviors and suicidal behaviors (suicide ideation and suicide attempt) in offspring. Interestingly, the problematic behaviors were further identified as a mediator in the multi-generational transmission of suicidal behaviors. Additionally, we observed alterations in brain structure within superior temporal gyrus (STG), precentral/postcentral cortex, posterior parietal cortex (PPC), cingulate cortex (CC), and planum temporale (PT), as well as disrupted functional connectivity of default mode network (DMN), ventral attention network (VAN), dorsal attention network (DAN), fronto-parietal network (FPN), and cingulo-opercular network (CON) among preadolescents with FHoS. These results provide compelling longitudinal evidence at the population level, highlighting the associations between multi-generational FHoS and maladaptive behavioral and neurodevelopmental outcomes in offspring. These findings underscore the need for early preventive measures aimed at mitigating the familial transmission of suicide risk and reducing the global burden of deaths among children and adolescents.

Predicting suicidality in late-life depression by 3D convolutional neural network and cross-sample entropy analysis of resting-state fMRI

BACKGROUND

Predicting suicide is a pressing issue among older adults; however, predicting its risk is difficult. Capitalizing on the recent development of machine learning, considerable progress has been made in predicting complex behavior such as suicide. As depression remained the strongest risk for suicide, we aimed to apply deep learning algorithms to identify suicidality in a group with late-life depression (LLD).

METHODS

We enrolled 83 patients with LLD, 35 of which were non-suicidal and 48 were suicidal, including 26 with only suicidal ideation and 22 with past suicide attempts, for resting-state functional magnetic resonance imaging (MRI). Cross-sample entropy (CSE) analysis was conducted to examine the complexity of MRI signals among brain regions. Three-dimensional (3D) convolutional neural networks (CNNs) were used, and the classification accuracy in each brain region was averaged to predict suicidality after sixfold cross-validation.

RESULTS

We found brain regions with a mean accuracy above 75% to predict suicidality located mostly in default mode, fronto-parietal, and cingulo-opercular resting-state networks. The models with right amygdala and left caudate provided the most reliable accuracy in all cross-validation folds, indicating their neurobiological importance in late-life suicide.

CONCLUSION

Combining CSE analysis and the 3D CNN, several brain regions were found to be associated with suicidality.

Impulsivity in Major Depressive Disorder Patients with Suicidal Ideation: Event-related Potentials in a GoNogo Task

Objective

: Suicidal ideation is one of the strongest predictors of suicide, and its relevance to impulsivity in depressed patients has been accumulated. Furthermore, high impulsivity patients show the attenuation of the Nogo amplitude in the GoNogo event-related potential (ERP). The purpose of the current study is to determine the correlation of Nogo ERP to the suicidal ideation depending on the condition of its presence or absence in major depressive disorder (MDD) patients.

Methods

: A total 162 participants (104 patients with suicidal ideation, 31 patients without suicidal ideation, and 27 healthy controls) were recruited, and performed GoNogo tasks during the electroencephalogram measurement. Depression, anxiety, suicidal ideation and impulsivity were assessed by self-rating scales. The clinical measures, behavioral data and Nogo ERP were compared among groups.

Results

: The MDD with suicidal ideation (SI) group showed significantly decreased Nogo P3 amplitudes compared to MDD without SI (Fz and Cz electrodes) and control group (all electrodes). The MDD with SI group also had significantly low accuracy of both Go and Nogo trails, compared to the MDD without group. The Nogo P3 amplitudes showed the negative relation to the scores of impulsivity, depression, anxiety and SI.

Conclusion

: Our results concluded that the Nogo P3 ERP amplitude was decreased in MDD patients with SI compared to MDD patients without SI and controls. These findings suggest that the decreased Nogo P3 amplitude is the one of the candidate biomarker for impulsivity in MDD patients to evaluating SI.

Associations of bullying perpetration and peer victimization subtypes with preadolescent's suicidality, non-suicidal self-injury, neurocognition, and brain development

BACKGROUND

Although both peer victimization and bullying perpetration negatively impact preadolescents' development, the underlying neurobiological mechanism of this adverse relationship remains unclear. Besides, the specific psycho-cognitive patterns of different bullying subtypes also need further exploration, warranting large-scale studies on both general bullying and specific bullying subtypes.

METHODS

We adopted a retrospective methodology by utilizing the data from the Adolescent Brain and Cognitive Development^SM Study (ABCD Study®) cohort collected between July 2018 and January 2021. Participants were preadolescents aged from 10 to 13 years. The main purpose of our study is to examine the associations of general and specific peer victimization/bullying perpetration with preadolescents' (1) suicidality and non-suicidal self-injury; (2) executive function and memory, including attention inhibition, processing speed, emotion working memory, and episodic memory; (3) brain structure abnormalities; and (4) brain network disturbances. Age, sex, race/ethnicity, body mass index (BMI), socioeconomic status (SES), and data acquisition site were included as covariates.

RESULTS

A total of 5819 participants aged from 10 to 13 years were included in this study. Higher risks of suicide ideation, suicide attempt, and non-suicidal self-injury were found to be associated with both bullying perpetration/peer victimization and their subtypes (i.e., overt, relational, and reputational). Meanwhile, poor episodic memory was shown to be associated with general victimization. As for perpetration, across all four tasks, significant positive associations of relational perpetration with executive function and episodic memory consistently manifested, yet opposite patterns were shown in overt perpetration. Notably, distinct psycho-cognitive patterns were shown among different subtypes. Additionally, victimization was associated with structural brain abnormalities in the bilateral paracentral and posterior cingulate cortex. Furthermore, victimization was associated with brain network disturbances between default mode network and dorsal attention network, between default mode network and fronto-parietal network, and ventral attention network related connectivities, including default mode network, dorsal attention network, cingulo-opercular network, cingulo-parietal network, and sensorimotor hand network. Perpetration was also associated with brain network disturbances between the attention network and the sensorimotor hand network.

CONCLUSIONS

Our findings offered new evidence for the literature landscape by emphasizing the associations of bullying experiences with preadolescents' clinical characteristics and cognitive functions, while distinctive psycho-cognitive patterns were shown among different subtypes. Additionally, there is evidence that these associations are related to neurocognitive brain networks involved in attention control and episodic retrieval. Given our findings, future interventions targeting ameliorating the deleterious effect of bullying experiences on preadolescents should consider their subtypes and utilize an ecosystemic approach involving all responsible parties.

Treatment response with ketamine in chronic suicidality: An open label functional connectivity study

BACKGROUND

Ketamine has recently been proposed as a treatment option for suicidality. Whilst its mechanism of action has been explored at molecular levels, the effect on the brain at the organ level remains unclear. Here we investigate immediate post-treatment and prolonged large-scale resting-state neural network changes to elucidate the neuronal underpinnings associated with ketamine's therapeutic effects.

METHODS

Twenty-eight adults (aged 22-72 years) participated in the Oral Ketamine Trial On Suicidality, which is an open-label trial of weekly sub-anaesthetic doses of oral ketamine over 6 weeks. MRI was acquired at baseline, post-treatment, and follow-up. Functional connectivity changes at post-treatment and follow-up were examined using seed based and independent component analysis.

RESULTS

The seed-based connectivity analysis revealed significantly reduced connectivity at post-treatment from the right hippocampus to both right and left superior frontal gyrus, from the left anterior parahippocampus to right superior frontal gyrus, left superior frontal gyrus, right middle frontal gyrus, and left frontal operculum cortex. Compared with baseline, the ICA showed reduced anterior default mode network connectivities to bilateral posterior cingulate cortex, middle and anterior cingulate cortex, lingual gyrus, and cuneus and increased connectivity of the frontoparietal network to the right superior parietal lobule at post-treatment.

LIMITATIONS

Open label pilot study.

CONCLUSIONS

We have shown sub-anaesthetic doses of ketamine alters connectivity in networks which have been shown to be aberrantly hyper-connected in numerous psychiatric conditions. These neurocircuitry changes are supported by significant reductions in suicide ideation. Our results provide support for the use of ketamine as a treatment for suicidality.

Age-related intrinsic functional connectivity underlying emotion utilization

Previous studies investigated the age-related positivity effect in terms of emotion perception and management, whereas little is known about whether the positivity effect is shown in emotion utilization (EU). If yes, the EU-related intrinsic functional connectivity and its age-associated alterations remain to be elucidated. In this study, we collected resting-state functional magnetic resonance imaging data from 62 healthy older adults and 72 undergraduates as well as their self-ratings of EU. By using the connectome-based predictive modeling (CPM) method, we constructed a predictive model of the positive relationship between EU self-ratings and resting-state functional connectivity. Lesion simulation analyses revealed that the medial-frontal network, default mode network, frontoparietal network, and subcortical regions played key roles in the EU-related CPM. Older subjects showed significantly higher EU self-ratings than undergraduates, which was associated with strengthened connectivity between the left dorsolateral prefrontal cortex and bilateral frontal poles, and between the left frontal pole and thalamus. A mediation analysis indicated that the age-related EU network mediated the age effect on EU self-ratings. Our findings extend previous research on the age-related "positivity effect" to the EU domain, suggesting that the positivity effect on the self-evaluation of EU is probably associated with emotion knowledge which accumulates with age.

Hampered gamma oscillations induced by sad emotion underlying suicide attempt in major depressive disorder

AIM

Major depressive disorder (MDD) is associated with high suicidality, especially for those with suicide attempt (SA). Although impaired oscillatory activity has been previously reported in patients with SA, little is known about precise temporal-spatial variability of its neural dynamics. To solve this, the current study probed the spectral power and network interactions underlying SA in MDD.

METHODS

The present study recruited 104 subjects including 56 subjects with MDD (30 with SA and 26 without SA) and 48 healthy controls, who performed sad expressions recognition task during magnetoencephalography (MEG) recording. By investigating source-reconstructed MEG-data, brain states representing different task stages were estimated from a Hidden Markov model. Spectrum power and network connectivity were compared via Gaussian Mixture Models, and fractional occupancy (FO) of states were compared via an independent F-test.

RESULTS

Brain states were corresponding to various frequencies (theta/beta/low gamma/ high gamma). In low gamma band (35-45 Hz), the early visual state exhibited increased activation and hyper inter-network connectivity between visual regions and the limbic system, while the middle fronto-parietal state exhibited attenuated activation and decreased intra-network connectivity within fronto-parietal regions in SA group. Crucially, FO values of these two states were significantly correlated with the suicide risks.

CONCLUSIONS

Suicide behavior of patients with MDD was significantly associated with aberrant oscillations in low gamma band. Elevated oscillations in occipital cortices and attenuated oscillations in fronto-parietal cortices were significantly associated with SA. Manifesting sadness indulging and reckless decision-making, the hampered temporal characteristics could help explain the neural-electric basis of SA.

Combined HTR1A/1B methylation and human functional connectome to recognize patients with MDD

OBJECTIVES

This study aimed to use a machine-learning method to identify HTR1A/1B methylation and resting-state functional connectivity (rsFC) related to the diagnosis of MDD, then try to build classification models for MDD diagnosis based on the identified features.

METHODS

Peripheral blood samples were collected from all recruited participants, and part of the participants underwent the resting-state fMRI scan. Features including HTR1A/1B methylation and rsFC were calculated. Then, the initial feature sets of epigenetics and neuroimaging were separately input into an all-relevant feature selection to generate significant discriminative power for MDD diagnosis. Random forest classifiers were constructed and evaluated based on identified features. In addition, the SHapley Additive exPlanations (SHAP) method was adapted to interpret the diagnostic model.

RESULTS

A combination of selected HTR1A/1B methylation and rsFC feature sets achieved better performance than using either one alone - a distinction between MDD and healthy control groups was achieved at 81.78% classification accuracy and 0.8948 AUC.

CONCLUSION

A high classification accuracy can be achieved by combining multidimensional information from epigenetics and cerebral radiomic features in MDD. Our approach can be helpful for accurate clinical diagnosis of MDD and further exploring the pathogenesis of MDD.

Transcutaneous auricular vagus nerve immediate stimulation treatment for treatment-resistant depression: A functional magnetic resonance imaging study

Objective

Transcutaneous auricular vagus nerve stimulation (taVNS) is effective for treatment-resistant depression (TRD). In the current study, we observed the immediate modulating brain effect of taVNS in patients with TRD using rest-state functional magnetic resonance imaging (rs-fMRI).

Method

Forty patients with TRD and forty healthy controls (HCs) were recruited. Rs-fMRI was performed before and after 30 min of taVNS at baseline. The brain regions that presented significantly different the Regional Homogeneity (ReHo) between the TRD patients and HCs were selected as the ROI to calculate the functional connectivity (FC) of full brain. The correlations were estimated between the clinical scales' score and the functional brain changes.

Results

Following taVNS stimulation treatment, TRD patients showed significantly reduced ReHo in the medial orbital frontal cortex (mOFC) (F = 18.06, P < 0.0001), ANCOVA of the mOFC-Based FC images revealed a significant interaction effect on the left inferior parietal gyrus (IPG) and left superior marginal gyrus (SMG) (F = 11.6615, P<0.001,F = 16.7520, P<0.0001). Among these regions, the HAMD and HAMA scores and ReHo/FC changes were not correlated.

Conclusion

This study applied rs-fMRI technology to examine the effect of taVNS stimulation treatment on the brain activity of TRD. These results suggest that the brain response of TRD patients to taVNS treatment may be associated with the functional modulation of cortical regions including the medial orbital frontal cortex, the left inferior parietal gyrus, and the left superior marginal regions. Changes in these neuroimaging indices may represent the neural mechanisms underlying taVNS Immediate Stimulation treatment in TRD.

Electrophysiological Changes Between Patients With Suicidal Ideation and Suicide Attempts: An Event-Related Potential Study

INTRODUCTION

Inhibitory control is regarded as an important ability related to the transition from suicidal ideation to suicide attempts. In event-related potential, patients with dysfunction of inhibitory control demonstrate a reduction in the no-go amplitude. This study aimed to determine the association between the no-go event-related potential component and suicidal behaviors among suicide attempters and ideators who never attempted suicide.

METHODS

Overall, 150 patients who visited the emergency room by suicide attempts or patients who visited the psychiatric department with suicidal ideation were recruited and instructed to perform a go/no-go task during electroencephalography recording. The Beck Depression Inventory, Beck Anxiety Inventory, Barratt Impulsivity Scale, Difficulties in Emotional Regulation Scale, and Acquired Capability for Suicide Scale were used. Individuals were divided into two groups: those with suicide attempt group) and with suicidal ideation (SI group) without SA. The psychological characteristics and event-related potentials of the two groups were compared. Correlation analyses were conducted to test the association between the clinical characteristics and event-related potentials.

RESULTS

The SA group had significantly decreased no-go P3 amplitudes at all electrodes compared to the SI group. In the correlation analysis between the clinical measurements and event-related potentials in all the participants, no-go P3 amplitudes in whole electrode sites were negatively correlated with the scores of the acquired capability for the suicide scale.

CONCLUSIONS

This study revealed that suicide attempters have dysfunction in controlling inhibition compared to suicide ideators reflected in the no-go P3. Our findings suggested that no-go P3 can be a biomarker associated suicide attempts in suicide ideators.