Fronto-limbic brain structures in suicidal and non-suicidal female patients with major depressive disorder

Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated With Suicidal Thoughts and Behaviors in Major Depressive Disorder

BACKGROUND

Although brain structural covariance network (SCN) abnormalities have been associated with suicidal thoughts and behaviors (STBs) in individuals with major depressive disorder (MDD), previous studies have reported inconsistent findings based on small sample sizes, and underlying transcriptional patterns remain poorly understood.

METHODS

Using a multicenter magnetic resonance imaging dataset including 218 MDD patients with STBs, 230 MDD patients without STBs, and 263 healthy control participants, we established individualized SCNs based on regional morphometric measures and assessed network topological metrics using graph theoretical analysis. Machine learning methods were applied to explore and compare the diagnostic value of morphometric and topological features in identifying MDD and STBs at the individual level. Brainwide relationships between STBs-related connectomic alterations and gene expression were examined using partial least squares regression.

RESULTS

Group comparisons revealed that SCN topological deficits associated with STBs were identified in the prefrontal, anterior cingulate, and lateral temporal cortices. Combining morphometric and topological features allowed for individual-level characterization of MDD and STBs. Topological features made a greater contribution to distinguishing between patients with and without STBs. STBs-related connectomic alterations were spatially correlated with the expression of genes enriched for cellular metabolism and synaptic signaling.

CONCLUSIONS

These findings revealed robust brain structural deficits at the network level, highlighting the importance of SCN topological measures in characterizing individual suicidality and demonstrating its linkage to molecular function and cell types, providing novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of suicide.

Brain Structural and Functional Damage Network Localization of Suicide

BACKGROUND

Extensive neuroimaging research on brain structural and functional correlates of suicide has produced inconsistent results. Despite increasing recognition that damage in multiple different brain locations that causes the same symptom can map to a common brain network, there is still a paucity of research investigating network localization of suicide.

METHODS

To clarify this issue, we initially identified brain structural and functional damage locations in relation to suicide from 63 published studies with 2135 suicidal and 2606 nonsuicidal individuals. By applying novel functional connectivity network mapping to large-scale discovery and validation resting-state functional magnetic resonance imaging datasets, we mapped these affected brain locations to 3 suicide brain damage networks corresponding to different imaging modalities.

RESULTS

The suicide gray matter volume damage network comprised widely distributed brain areas primarily involving the dorsal default mode, basal ganglia, and anterior salience networks. The suicide task-induced activation damage network was similar to but less extensive than the gray matter volume damage network, predominantly implicating the same canonical networks. The suicide resting-state activity damage network manifested as a localized set of brain regions encompassing the orbitofrontal cortex and middle cingulate cortex.

CONCLUSIONS

Our findings not only may help reconcile prior heterogeneous neuroimaging results, but also may provide insights into the neurobiological mechanisms of suicide from a network perspective, which may ultimately inform more targeted and effective strategies to prevent suicide.

Role of fronto-limbic circuit in neuropsychiatric symptoms of dementia: clinical evidence from an exploratory study

Background

Neuropsychiatric symptoms (NPSs) are a distressful aspect of dementia and the knowledge of structural correlates of NPSs is limited. We aimed to identify associations of fronto-limbic circuit with specific NPSs in patients with various types of cognitive impairment.

Methods

Of 84 participants, 27 were diagnosed with mild cognitive impairment (MCI), 41 with Alzheimer's disease (AD) dementia and 16 with non-AD dementia. In all patients we assessed regional brain morphometry using a region of interest (ROI)-based analysis. The mean cortical thickness (CT) of 20 cortical regions and the volume (V) of 4 subcortical areas of the fronto-limbic system were extracted. NPSs were rated with the Neuropsychiatric Inventory (NPI). We used multiple linear regression models adjusted for age and disease duration to identify significant associations between scores of NPI sub-domains and MRI measures of brain morphometry.

Results

All significant associations found were negative, except those between irritability and the fronto-opercular regions in MCI patients (corresponding to a 40-50% increase in CT) and between delusions and hippocampus and anterior cingulate gyrus (with a 40-60% increase). Apathy showed predominant involvement of the inferior frontal regions in AD group (a 30% decrease in CT) and of the cingulate cortex in non-AD group (a 50-60% decrease in CT). Anxiety correlated in MCI patients with the cingulate gyrus and caudate, with a CT and V decrease of about 40%, while hallucinations were associated with left enthorinal gyrus and right amygdala and temporal pole. Agitation showed associations in the AD group with the frontal regions and the temporal pole, corresponding to a 30-40% decrease in CT. Euphoria, disinhibition and eating abnormalities were associated in the MCI group with the entorhinal, para-hippocampal and fusiform gyri, the temporal pole and the amygdala (with a 40-70% decrease in CT and V). Finally, aberrant motor behavior reported a significant association with frontal and cingulate regions with a 50% decrease in CT.

Conclusion

Our findings indicate that specific NPSs are associated with the structural involvement of the fronto-limbic circuit across different types of neurocognitive disorders. Factors, such as age and disease duration, can partly account for the variability of the associations observed.

Disrupted small-world white matter networks in patients with major depression and recent suicide plans or attempts

Suicide is a major concern for health, and depression is an established proximal risk factor for suicide. This study aimed to investigate white matter features associated with suicide. We constructed white matter structural networks by deterministic tractography via diffusion tensor imaging in 51 healthy controls, 47 depressed patients without suicide plans or attempts and 56 depressed patients with suicide plans or attempts. Then, graph theory analysis was used to measure global and nodal network properties. We found that local efficiency was decreased and path length was increased in suicidal depressed patients compared to healthy controls and non-suicidal depressed patients; moreover, the clustering coefficient was decreased in depressed patients compared to healthy controls; and the global efficiency and normalized characteristic path length was increased in suicidal depressed patients compared to healthy controls. Similarly, compared with those in non-suicidal depressed patients, nodal efficiency in the thalamus, caudate, medial orbitofrontal cortex, hippocampus, olfactory cortex, supplementary motor area and Rolandic operculum was decreased. In summary, compared with those of non-suicidal depressed patients, the structural connectome of suicidal depressed patients exhibited weakened integration and segregation and decreased nodal efficiency in the fronto-limbic-basal ganglia-thalamic circuitry. These alterations in the structural networks of depressed suicidal brains provide insights into the underlying neurobiology of brain features associated with suicide.

Grey matter abnormalities in major depressive disorder patients with suicide attempts: A systematic review of age-specific differences

Background

Previous studies have reported alterations in brain structure in major depressive disorder (MDD) patients with suicide attempts. However, age-related changes in suicidal MDD patients remain unclear.

Methods

We performed a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Embase, PubMed, and Web of Science were searched to identify relevant studies from inception to January 2023. All voxel-based and surface-based morphometry studies comparing suicidal MDD patients to MDD or healthy controls were included. Studies were then grouped by age range (old, middle-age, adolescent) and the commonalities and age-related structural brain alterations were summarized. The included studies were evaluated using the Newcastle-Ottawa Scale (NOS).

Results

A total of 17 studies met the inclusion criteria, including 3 of late-life depression (LLD) patients, 11 of middle-aged depression (MAD) patients, and 3 of adolescent depression (AOD) patients. The majority of studies had moderate to high NOS scores, indicating good quality. Patients in all three age groups exhibited extensive alterations in the lateral, medial, and orbital regions of the frontal lobes. Furthermore, suicidal MAD patients showed a specific decrease in the gray matter volume of the dorsolateral prefrontal cortex compared to suicidal LLD patients. Cortical thickness and left angular gyrus volume were decreased in suicidal MAD and suicidal LLD patients, but increased in suicidal AOD patients.

Conclusion

This systematic review summarizes structural brain changes in suicidal MDD patients at three age groups: elderly, middle-aged, and adolescent. These findings help elucidate the common circuitry of MDD related to suicide over the lifespan and highlight unique circuitry associated with different ages. These findings may help predict the risk of suicide in MDD patients at different ages.

The altered temporal properties of dynamic functional connectivity associated with suicide attempt in bipolar disorders

OBJECTIVE

The suicide risk in bipolar disorder (BD) is the highest among psychiatric disorders, and the neurobiological mechanism of suicide in BD remains unclear. The study aimed to investigate the underlying relevance between the implicated abnormalities of dynamic functional connectivity (FC) and suicide attempt (SA) in BD.

METHODS

We used the sliding window method to analyze the dynamic FC patterns from resting-state functional MRI data in 81 healthy controls (HC) and 114 BD patients (50 with SA and 64 with none SA). Then, the temporal properties of dynamic FC and the relationship between altered measures and clinical variables were explored.

RESULTS

We found that one of the five captured brain functional states was more associated with SA. The SA patients showed significantly increased fractional window and dwell time in the suicide-related state, along with increased number of state transitions compared with none SA (NSA). In addition, the connections within subcortical network-subcortical network (SubC-SubC), default mode network-subcortical network (DMN-SubC), and attention network-subcortical network (AN-SubC) were significantly changed in SA patients relative to NSA and HC in the suicide-related state. Crucially, the above-altered measures were significantly correlated with suicide risk.

CONCLUSIONS

Our findings suggested that the impaired dynamic FC within SubC-SubC, DMN-SubC, and AN-SubC were the important underlying mechanism in understanding SA for BD patients. It highlights the temporal properties of whole-brain dynamic FC could serve as the valuable biomarker for suicide risk assessment in BD.

Functional Abnormality of the Reward System in Depressed Adolescents and Young Adults with and without Suicidal Behavior

OBJECTIVE

To identify local and functional connectivity abnormalities in the brain's reward network in depressed adolescents and young adults with and without suicidal behavior.

METHODS

Magnetic resonance imaging data were obtained from 41 major depressive disorder (MDD) patients with suicidal behavior (sMDD, males/females: 12/29), 44 MDD patients without suicidal behavior (nMDD, males/females: 13/32), and 52 healthy controls (HCs, males/females: 17/35). The Young Mania Scale, Hamilton Depression Scale, Columbia Suicide Scale, and Scale for Suicide Ideation were used to evaluate emotional state and suicidal ideation and behaviors. The amplitude of low frequency fluctuations (ALFF), regional homogeneity (ReHo) and functional connectivity of 11 regions of interest (ROIs) in the reward network were determined.

RESULTS

ALFF values in the vmPFC of the nMDD group were significantly lower than those in the HC group (p = 0.031). The ReHo values of the nMDD group were lower in the lVS but higher in the vmPFC than those of the HC group (P = 0.018 and 0.025, respectively). Functional connectivity of the AC with the vmPFC, lVS, rVS, and vmPFC was increased in the sMDD group compared with that in the nMDD group (P = 0.038, 0.034, 0.006, respectively).

CONCLUSION

Local and functional connectivity abnormalities in the reward network were found in the MDD groups. However, increased functional connectivity was found in only the sMDD group.

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.

Connectomics-based resting-state functional network alterations predict suicidality in major depressive disorder

Suicidal behavior is a major concern for patients who suffer from major depressive disorder (MDD). However, dynamic alterations and dysfunction of resting-state networks (RSNs) in MDD patients with suicidality have remained unclear. Thus, we investigated whether subjects with different severity of suicidal ideation and suicidal behavior may have different disturbances in brain RSNs and whether these changes could be used as the diagnostic biomarkers to discriminate MDD with or without suicidal ideation and suicidal behavior. Then a multicenter, cross-sectional study of 528 MDD patients with or without suicidality and 998 healthy controls was performed. We defined the probability of dying by the suicide of the suicidality components as a 'suicidality gradient'. We constructed ten RSNs, including default mode (DMN), subcortical (SUB), ventral attention (VAN), and visual network (VIS). The network connections of RSNs were analyzed among MDD patients with different suicidality gradients and healthy controls using ANCOVA, chi-squared tests, and network-based statistical analysis. And support vector machine (SVM) model was designed to distinguish patients with mild-to-severe suicidal ideation, and suicidal behavior. We found the following abnormalities with increasing suicidality gradient in MDD patients: within-network connectivity values initially increased and then decreased, and one-versus-other network values decreased first and then increased. Besides, within- and between-network connectivity values of the various suicidality gradients are mainly negatively correlated with HAMD anxiety and positively correlated with weight. We found that VIS and DMN-VIS values were affected by age (p < 0.05), cingulo-opercular network, and SUB-VAN values were statistically influenced by sex (p < 0.05). Furthermore, the SVM model could distinguish MDD patients with different suicidality gradients (AUC range, 0.73-0.99). In conclusion, we have identified that disrupted brain connections were present in MDD patients with different suicidality gradient. These findings provided useful information about the pathophysiological mechanisms of MDD patients with suicidality.

Classification of suicidality by training supervised machine learning models with brain MRI findings: A systematic review

BACKGROUND

Suicide is a global public health issue causing around 700,000 deaths worldwide each year. Therefore, identifying suicidal thoughts and behaviors in patients can help lower the suicide-related mortality rate. This review aimed to investigate the feasibility of suicidality identification by applying supervised Machine Learning (ML) methods to Magnetic Resonance Imaging (MRI) data.

METHODS

We conducted a systematic search on PubMed, Scopus, and Web of Science to identify studies examining suicidality by applying ML methods to MRI features. Also, the Prediction Model Risk of Bias Assessment Tool (PROBAST) was employed for the quality assessment.

RESULTS

23 studies met the inclusion criteria. Of these, 20 developed prediction models without external validation and 3 developed prediction models with external validation. The performance of ML models varied among the reviewed studies, with the highest reported values of accuracies and Area Under the Curve (AUC) ranging from 51.7 % to 100 % and 0.52 to 1, respectively. Over half of the studies that reported accuracy (12/21) or AUC (13/16) achieved values of ≥0.8. Our comparative analysis indicated that deep learning exhibited the highest predictive performance compared to other ML models. The most commonly identified discriminative imaging features were resting-state functional connectivity and grey matter volume within prefrontal-limbic structures.

LIMITATIONS

Small sample sizes, lack of external validation, heterogeneous study designs, and ML model development.

CONCLUSIONS

Most of the studies developed ML models capable of ML-based suicide identification, although ML models' predictive performance varied across the reviewed studies. Thus, further well-designed is necessary to uncover the true potential of different ML models in this field.

Estimating a brain network predictive of stress and genotype with supervised autoencoders

Targeted brain stimulation has the potential to treat mental illnesses. We develop an approach to help design protocols by identifying relevant multi-region electrical dynamics. Our approach models these dynamics as a superposition of latent networks, where the latent variables predict a relevant outcome. We use supervised autoencoders (SAEs) to improve predictive performance in this context, describe the conditions where SAEs improve predictions, and provide modelling constraints to ensure biological relevance. We experimentally validate our approach by finding a network associated with stress that aligns with a previous stimulation protocol and characterizing a genotype associated with bipolar disorder.

Aberrant brain entropy in posttraumatic stress disorder comorbid with major depressive disorder during the coronavirus disease 2019 pandemic

Aim

Previously, neuroimaging studies on comorbid Posttraumatic-Major depression disorder (PTSD-MDD) comorbidity found abnormalities in multiple brain regions among patients. Recent neuroimaging studies have revealed dynamic nature on human brain activity during resting state, and entropy as an indicator of dynamic regularity may provide a new perspective for studying abnormalities of brain function among PTSD-MDD patients. During the COVID-19 pandemic, there has been a significant increase in the number of patients with PTSD-MDD. We have decided to conduct research on resting-state brain functional activity of patients who developed PTSD-MDD during this period using entropy.

Methods

Thirty three patients with PTSD-MDD and 36 matched TCs were recruited. PTSD and depression symptoms were assessed using multiple clinical scales. All subjects underwent functional magnetic resonance imaging (fMRI) scans. And the brain entropy (BEN) maps were calculated using the BEN mapping toolbox. A two-sample t-test was used to compare the differences in the brain entropy between the PTSD-MDD comorbidity group and TC group. Furthermore, correlation analysis was conducted between the BEN changes in patients with PTSD-MDD and clinical scales.

Results

Compared to the TCs, PTSD-MDD patients had a reduced BEN in the right middle frontal orbital gyrus (R_MFOG), left putamen, and right inferior frontal gyrus, opercular part (R_IFOG). Furthermore, a higher BEN in the R_MFOG was related to higher CAPS and HAMD-24 scores in the patients with PTSD-MDD.

Conclusion

The results showed that the R_MFOG is a potential marker for showing the symptom severity of PTSD-MDD comorbidity. Consequently, PTSD-MDD may have reduced BEN in frontal and basal ganglia regions which are related to emotional dysregulation and cognitive deficits.

Reduced corticolimbic habituation to negative stimuli characterizes bipolar depressed suicide attempters

Suicide attempts in Bipolar Disorder are characterized by high levels of lethality and impulsivity. Reduced rates of amygdala and cortico-limbic habituation can identify a fMRI phenotype of suicidality in the disorder related to internal over-arousing states. Hence, we investigated if reduced amygdala and whole-brain habituation may differentiate bipolar suicide attempters (SA, n = 17) from non-suicide attempters (nSA, n = 57), and healthy controls (HC, n = 32). Habituation was assessed during a fMRI task including facial expressions of anger and fear and a control condition. Associations with suicidality and current depressive symptomatology were assessed, including machine learning procedure to estimate the potentiality of habituation as biomarker for suicidality. SA showed lower habituation compared to HC and nSA in several cortico-limbic areas, including amygdalae, cingulate and parietal cortex, insula, hippocampus, para-hippocampus, cerebellar vermis, thalamus, and striatum, while nSA displayed intermediate rates between SA and HC. Lower habituation rates in the amygdalae were also associated with higher depressive and suicidal current symptomatology. Machine learning on whole-brain and amygdala habituation differentiated SA vs. nSA with 94% and 69% of accuracy, respectively. Reduced habituation in cortico-limbic system can identify a candidate biomarker for attempting suicide, helping in detecting at-risk bipolar patients, and in developing new therapeutic interventions.

Brain structural abnormalities and trait impulsivity in suicidal and non-suicidal patients with bipolar disorder

BACKGROUND

Impulsivity is a characteristic of patients with bipolar disorder (BD) and may result in a higher risk of suicide attempt (SA). Although brain structural abnormalities have been suggested in the pathophysiology of BD, the relationship to impulsivity and suicide in BD is still not clear.

METHODS

52 euthymic patients with BD (26 of them had a history of SA) and 56 age- and sex-matched healthy controls were recruited. All participants received clinical assessment, including Barratt impulsiveness scale (BIS), and underwent structural magnetic resonance imaging examination. An automated surface-based method (FreeSurfer) was used to measure brain volume and cortical surface area. A general linear model was applied to analyze the association between brain-wise greater gray matter volume (GMV), surface area and BIS scores separately for BD patients with and without SA history.

RESULTS

BD patients with SA history scored higher in BIS total score and subscores in attention, motor, cognitive complexity and cognitive instability than those without SA history and controls (all p < 0.01). In patients with SA history, higher BIS scores were associated with greater GMV in the left pars triangularis and greater surface area in left pars opercularis (all p < 0.01). BD patients with SA history showed a greater GMV in inferior frontal gyrus than patients without SA history (p < 0.05).

LIMITATION

The cross-sectional design precluded examination of chronological relationships of SA, brain structural abnormalities, and trait impulsivity among BD.

CONCLUSIONS

The findings indicate that the prefrontal cortex, especially the left inferior frontal gyrus, plays a vital role in trait impulsivity and suicidal behavior among patients with BD.

Cognitive impairment and factors influencing depression in adolescents with suicidal and self-injury behaviors: a cross-sectional study

BACKGROUND

Non-suicidal self-injury (NSSI) and suicide attempts (SAs) by adolescent patients with depression have become serious public health problems. There is still insufficient research evidence on the effects of NSSI and SAs on neurocognitive functioning in adolescents. Cognitive function alterations may be associated with SAs and self-injury. NSSI and SAs have different influencing factors.

METHODS

Participants were recruited from outpatient clinics and included 142 adolescent patients with depression (12-18 years old). This cohort included the SAs group (n = 52), NSSI group (n = 65), and depression without SAs/NSSI control group (n = 25). All participants underwent a clinical interview and neuropsychological assessment for group comparisons, and post-hoc tests were performed. Finally, partial correlation analysis was used to explore factors related to changes in cognitive function.

RESULTS

The SAs group performed significantly worse than the control group in executive function and working memory. The depression score was directly proportional to the executive function of the SAs group, whereas cognitive functioning in the NSSI group was associated with borderline traits and rumination.

CONCLUSIONS

These findings suggest that impairment of executive function and working memory may be a common pattern in adolescent depressed patients with SAs. However, borderline traits and rumination may be indicative of NSSI but not SAs.

History of suicide attempt associated with amygdala and hippocampus changes among individuals with schizophrenia

Abnormalities in subcortical brain structures may reflect higher suicide risk in mood disorders, but less is known about its associations for schizophrenia. This cross-sectional imaging study aimed to explore whether the history of suicide attempts was associated with subcortical changes among individuals with schizophrenia. We recruited 44 individuals with schizophrenia and a history of suicide attempts (SZ-SA) and 44 individuals with schizophrenia but without a history of suicide attempts (SZ-NSA) and 44 healthy controls. Linear regression showed that SZ-SA had smaller volumes of the hippocampus (Cohen's d = -0.72), the amygdala (Cohen's d = -0.69), and some nuclei of the amygdala (Cohen's d, -0.57 to -0.72) than SZ-NSA after adjusting for age, sex, illness phase, and intracranial volume. There was no difference in the volume of the subfields of the hippocampus. It suggests the history of suicide attempts is associated with subcortical volume alterations in schizophrenia.

Machine learning based identification of structural brain alterations underlying suicide risk in adolescents

Suicide is the third leading cause of death for individuals between 15 and 19 years of age. The high suicide mortality rate and limited prior success in identifying neuroimaging biomarkers indicate that it is crucial to improve the accuracy of clinical neural signatures underlying suicide risk. The current study implements machine-learning (ML) algorithms to examine structural brain alterations in adolescents that can discriminate individuals with suicide risk from typically developing (TD) adolescents at the individual level. Structural MRI data were collected from 79 adolescents who demonstrated clinical levels of suicide risk and 79 demographically matched TD adolescents. Region-specific cortical/subcortical volume (CV/SCV) was evaluated following whole-brain parcellation into 1000 cortical and 12 subcortical regions. CV/SCV parameters were used as inputs for feature selection and three ML algorithms (i.e., support vector machine [SVM], K-nearest neighbors, and ensemble) to classify adolescents at suicide risk from TD adolescents. The highest classification accuracy of 74.79% (with sensitivity = 75.90%, specificity = 74.07%, and area under the receiver operating characteristic curve = 87.18%) was obtained for CV/SCV data using the SVM classifier. Identified bilateral regions that contributed to the classification mainly included reduced CV within the frontal and temporal cortices but increased volume within the cuneus/precuneus for adolescents at suicide risk relative to TD adolescents. The current data demonstrate an unbiased region-specific ML framework to effectively assess the structural biomarkers of suicide risk. Future studies with larger sample sizes and the inclusion of clinical controls and independent validation data sets are needed to confirm our findings.

Suicide risk stratification among major depressed patients based on a machine learning approach and whole-brain functional connectivity

BACKGROUND

Suicide risk stratification and individual-level prediction among major depressive disorder (MDD) is important but unrecognized. Here, we construct models to detect suicidality in MDD using machine learning (ML) and whole-brain functional connectivity (FC).

METHODS

A cross-sectional assessment was conducted on 200 subjects, including 126 MDD with high suicide risk (HSR; 73 patients with suicidal ideation [SI], 53 patients with suicidal attempts [SA]), 36 patients with low suicide risk (LSR) and 38 healthy controls (HCs). Whole-brain FC features were calculated, the least absolute shrinkage and selection operator (LASSO) method was used for feature selection. A support vector machine (SVM) was performed to build models to distinguish MDD from HCs, and for suicide risk stratification among MDD. Leave-one-out cross-validation (LOOCV) was performed for validation.

RESULTS

The models constructed using SVM on whole-brain FC had powerful classification efficiency in screening MDD from HCs (accuracy = 88.50 %), and in suicide risk stratification among MDD patients (with accuracy = 84.56 % and 74.60 % in classifying patients with HSR or LSR, and SA or SI, respectively). Subsequent analysis demonstrated that intra-network dysconnectivity in the sensorimotor network and inter-network dysconnectivity between the default and dorsal attention network could characterize HSR and SA in MDD, separately.

LIMITATIONS

This study was a single center cohort study without external validation.

CONCLUSION

These findings indicate ML approaches are useful in suicide risk stratification among MDD based on whole-brain FC, which may help to identify individuals with different suicide risks in MDD and provide an individual-level prediction.

Individualized Functional Connectome Identified Replicable Biomarkers for Dysphoric Symptoms in First-Episode Medication-Naïve Patients With Major Depressive Disorder

BACKGROUND

Major depressive disorder (MDD) is a heterogeneous syndrome and can be conceptualized as a mixture of dimensional abnormalities across several specific brain circuits. The neural underpinnings of different symptom dimensions in MDD are not well understood. We aimed to identify robust, generalizable, functional connectivity (FC)-based biomarkers for different symptom dimensions in MDD using individualized functional connectomes.

METHODS

Patterns of FC associated with symptom severity were identified using a novel, individualized, functional network parcellation analysis in conjunction with hierarchical clustering. Dimension-specific prediction models were trained to estimate symptom severity in first-episode medication-naïve patients (discovery dataset, n = 95) and replicated in an independent validation dataset (n = 94). The correlation between FC changes and symptom changes was further explored in a treatment dataset (n = 55).

RESULTS

Two distinct symptom clusters previously identified in patients with MDD, namely dysphoric and anxiosomatic clusters, were robustly replicated in our data. A connectivity biomarker associated with dysphoric symptoms was identified, which mainly involved the default, dorsal attention, and limbic networks. Critically, this brain-symptom association was confirmed in the validation dataset. Moreover, the marker also tracked dysphoric symptom improvement following a 2-week antidepressant treatment. For comparison, we repeated our analyses using a nonindividualized approach and failed to identify replicable brain-symptom biomarkers. Further quantitative analysis indicated that the generalizability of the connectivity-symptom association was hampered when functional regions were not localized in individuals.

CONCLUSIONS

This work reveals robust, replicable FC biomarkers for dysphoric symptoms in MDD, demonstrates the advantage of individual-oriented approach, and emphasizes the importance of independent validation in psychiatric neuroimaging analysis.

The associations between suicide-related behaviors, prefrontal dysfunction in emotional cognition, and personality traits in mood disorders

Suicide is a serious public health problem, and it is urgent to identify biomarkers associated with suicide to prevent it. We aimed to clarify the association across suicidal behavior, personality traits, and brain activation by emotional stimulation tasks using near-infrared spectroscopy (NIRS) in patients with mood disorders. 11 mood disorder patients with a history of suicide attempt (MDSA), 18 mood disorder patients with no history of suicide attempt (MDNSA), and 17 healthy individuals were studied. The MDSA patients showed significantly high impulsivity and hopeless compared to healthy subjects, great response to the thread word task in the orbitofrontal cortex (OFC) and dorsolateral prefrontal cortex (DLPFC) compared to MDNSA patients, and the significant correlation between the personality traits and brain activation. The MDNSA did not show the trend. The results suggest that the personality traits and the activation of OFC and DLPFC during the negative emotional cognitive stimuli is associated with suicidal behavior, indicating the findings are involved in the pathophysiology of suicidality in mood disorders.

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.

Resting-state functional connectivity of the amygdala in major depressive disorder with suicidal ideation

Suicide is a common issue among major depressive disorder (MDD) patients and suicidal ideation (SI) is the first step toward it. There are no definitive objective biomarkers of SI relative to MDD. In this study, a seed-based correlation analysis was performed among 36 MDD patients with SI, 66 MDD patients without SI (NSI), and 57 healthy controls (HCs) using amygdala resting-state functional connectivity (RSFC). Furthermore, the correlation between amygdala RSFC and clinical features was examined in the SI group. When compared to the NSI group, SI group exhibited increased RSFC between the left amygdala seed and left medial superior frontal gyrus (SFGmed) as well as left middle frontal gyrus (MFG). In turn, a decreased RSFC was observed between the left amygdala seed and the following brain regions including the left inferior parietal lobule (IPL), right precentral gyrus (PrCG), and left superior parietal lobule (SPL) in SI group compared to NSI group. Moreover, the SI group exhibited increased RSFC of the right amygdala with left middle temporal gyrus (MTG); In addition, the RSFC of the left amygdala with left MFG was negatively associated with learning and memory (VSM), speed of processing (SOP). The RSFC of the amygdala is distinct between MDD patients with SI and without SI. Our findings reveal the neurobiological characteristics of MDD with respect to SI and provide new clues regarding vulnerability to mental illness. It is necessary to carry out repeated and more longitudinal researches using multimodal approaches on SI in the future.

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.

Association between the volume of subregions of the amygdala and major depression with suicidal thoughts and anxiety in a Chinese cohort

BACKGROUND

Major depression is the largest single contributor to suicide, and anxiety symptoms are associated with the severity of depression and suicidality. It is important to explore biomarkers of anxiety and suicidal ideation in major depression. In this study we hypothesized that the volume of subregions of the amygdala might be indicators of anxiety and suicidal ideation in patients with major depression.

METHODS

We recruited 59 drug-naïve patients with first-episode depression who scored >17 on the Hamilton Rating Scale for depression, and 30 healthy controls to participate in a magnetic resonance imaging study. We examined the volume of sub-regions of the amygdala thought to be involved in processing anxious emotion in the depression and healthy control groups. We performed pair-wise comparisons of amygdala subfield volumes in patients with depression and healthy controls with an analysis of variance. We used logistic regression to test the relationship between suicidal ideation and anxious character with the volume of subregions of the amygdala.

RESULTS

1) We found a significant difference in the volumes of the left amygdala (P = 0.003) and right amygdala (P = 0.001) between the two groups. There are significant differences in the volumes of the sub-region of the left amygdala. 2) The volume of the left lateral nucleus (P<0.001), basal nucleus (P<0.001), accessory basal nucleus (P<0.05), left Paralaminar-nucleus (P<0.001), right lateral-nucleus (P<0.05), right basal-nucleus (P<0.05), right anterior-amygdaloid area AAA (P<0.05), right paralaminar-nucleus (P<0.001) in the depression group are larger than healthy controls, however the volumes of the central-nucleus (P<0.05), medial-nucleus (P<0.001) in both sides are decreased in the major depression group. 3) There is a significantly larger volume of right medial nucleus in the suicidal ideation group comparing the hopelessness (P = 0.026), and the depressive patients without hopeless thoughts (P = 0.004). 4) We found a negative relation between the left basal nucleus and anxiety (OR: 0.940, 95%CI: 0.891-0.991), and a positive relation between the accessory basal nucleus on the left side and anxiety (OR: 1.007, 95%CI: 1.002-1.158).

LIMITATIONS

We were not able to examine the effects of gender or age. The changes of amygdala volume in patients with depression were not followed up. Our sample size was such that independent replication is needed to confirm the robustness of our results.

CONCLUSIONS

The volumes of the basal nucleus in both sides are increased in depressed patients while the volumes of the central-nucleus, medial-nucleus bilaterally are reduced in the major depression group. Among the subregions, the volume of right medial nucleus might be the biomarkers for suicidal ideation in depressive patients.

Altered Regional Homogeneity and Amplitude of Low-Frequency Fluctuations Induced by Electroconvulsive Therapy for Adolescents with Depression and Suicidal Ideation

Resting-state functional magnetic resonance imaging (rs-fMRI) was used to investigate the effects of electroconvulsive therapy (ECT) causing brain function changes in adolescents who suffered from depression and suicidal ideation (SI). A total of 30 patients (MDDs) and 25 healthy controls (HCs) matched by gender, age, and education level were enrolled. The amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo) were used to compare differences between HCs and MDDs at baseline, and differences in ALFF and ReHo pre/post ECT in MDDs. Pearson correlation analysis was used to evaluate the relationship between altered brain function and clinical symptoms. At baseline, MDDs showed decreased ALFF in the left inferior temporal gyrus and right amygdala, decreased ReHo in left inferior temporal gyrus, and increased ReHo in the right inferior frontal gyrus, opercular part and left middle occipital gyrus. After ECT, MDDs showed increased ALFF in the right middle occipital gyrus, decreased ALFF in left temporal pole, left inferior frontal gyrus, opercular part, and right frontal middle gyrus, increased ReHo in the right middle occipital gyrus, and left inferior temporal gyrus. Pearson correlation found HAMD scores at baseline were negatively correlated with ALFF in the left inferior temporal gyrus, and HAMD and BSSI scores after ECT were negatively correlated with ALFF in the right middle occipital gyrus. The abnormal activities of amygdala, inferior temporal gyrus and middle occipital gyrus might be related to depressive and suicidal symptoms in adolescents.

Dynamic connectivity alterations in anterior cingulate cortex associated with suicide attempts in bipolar disorders with a current major depressive episode

OBJECTIVE

Considering that the physiological mechanism of the anterior cingulate cortex (ACC) in suicide brain remains elusive for bipolar disorder (BD) patients. The study aims to investigate the intrinsic relevance between ACC and suicide attempts (SA) through transient functional connectivity (FC).

METHODS

We enrolled 50 un-medicated BD patients with at least one SA, 67 none-suicide attempt patients (NSA) and 75 healthy controls (HCs). The sliding window approach was utilized to study the dynamic FC of ACC via resting-state functional MRI data. Subsequently, we probed into the temporal properties of dynamic FC and then estimated the relationship between dynamic characteristics and clinical variables using the Pearson correlation.

RESULTS

We found six distinct FC states in all populations, with one of them being more associated with SA. Compared with NSA and HCs, the suicide-related functional state showed significantly reduced dwell time in SA patients, accompanied by a significantly increased FC strength between the right ACC and the regions within the subcortical (SubC) network. In addition, the number of transitions was significantly increased in SA patients relative to other groups. All these altered indicators were significantly correlated with the suicide risk.

CONCLUSIONS

The results suggested that the dysfunction of ACC was relevant to SA from a dynamic FC perspective in BD patients. It highlights the temporal properties in dynamic FC of ACC that could be used as a putative target of suicide risk assessment for BD patients.

Association of disease course and brain structural alterations in major depressive disorder

INTRODUCTION

The investigation of disease course-associated brain structural alterations in Major Depressive Disorder (MDD) have resulted in heterogeneous findings, possibly due to low reliability of single clinical variables used for defining disease course. The present study employed a principal component analysis (PCA) on multiple clinical variables to investigate effects of cumulative lifetime illness burden on brain structure in a large and heterogeneous sample of MDD patients.

METHODS

Gray matter volumes (GMV) was estimated in n = 681 MDD patients (mean age: 35.87 years; SD = 12.89; 66.6% female) using voxel-based-morphometry. Five clinical variables were included in a PCA to obtain components reflecting disease course to associate resulting components with GMVs.

RESULTS

The PCA yielded two main components: Hospitalization reflected by patients' frequency and duration of inpatient treatment and Duration of Illness reflected by the frequency and duration of depressive episodes. Hospitalization revealed negative associations with bilateral dorsolateral prefrontal cortex (DLPFC) and left insula volumes. Duration of Illness showed significant negative associations with left hippocampus and right DLPFC volumes. Results in the DLPFC and hippocampus remained significant after additional control for depressive symptom severity, psychopharmacotherapy, psychiatric comorbidities, and remission status.

CONCLUSION

This study shows that a more severe and chronic lifetime disease course in MDD is associated with reduced volume in brain regions relevant for executive and cognitive functions and emotion regulation in a large sample of patients representing the broad heterogeneity of MDD disease course. These findings were only partly influenced by other clinical characteristics (e.g., remission status, psychopharmacological treatment).

Aberrant integrity of the cortico-limbic-striatal circuit in major depressive disorder with suicidal ideation

BACKGROUND

Suicidal ideation is a common symptom of major depressive disorder (MDD) that reflects a cognitive alteration in the background of intense emotional dysregulation. Amygdala is a critical emotion processing center that facilitates moving from emotional appraisal to action. However, whether MDD patients with suicidal ideation show dysconnectivity of the amygdala within a large-scale neurocognitive circuitry remains unknown.

METHODS

Participants were 22 MDD patients without suicidal ideation (MDD-NSI), 59 MDD patients with suicidal ideation (MDD-SI), and 60 healthy controls (HCs). We compared the amygdala-based resting-state functional connectivity of four amygdala subregions across the three groups. We selected brain regions with significant between-group differences in amygdalar conectivity as the regions of interest (ROI) and performed ROI-to-ROI and graph-theoretical analyses to explore dysconnectivity patterns at various granularity levels.

RESULTS

Brain regions showing omnibus differences across the three groups were distributed across a cortico-limbic-striatal circuitry. MDD-SI had unique dysconnectivity of the lateral amygdala with caudate, middle temporal gyrus, and postcentral gyrus compared with the other two groups. MDD-SI and MDD-NSI had shared dysconnectivity of the medial amygdala with medial superior frontal gyrus and middle temporal gyrus. Within the derived cortico-limbic-striatal circuitry, MDD-SI exhibited lower global connectivity, reduced sigma (small-worldness), but increased lambda (path-length) than HCs. Reduced sigma correlated with increased severity of suicidal ideation. We achieved high classification accuracy (84.09%, with AUC 0.82) in distinguishing MDD-SI from MDD-NSI.

CONCLUSIONS

Aberrant integrity of the cortico-limbic-striatal circuit centered on the amygdala provides a promising neural substrate for suicidal ideation that requires further investigation in MDD.

Distinct patterns of altered quantitative T1ρ and functional BOLD response associated with history of suicide attempts in bipolar disorder

Despite the high risk for suicide, relatively few studies have explored the relationship between suicide and brain imaging measures in bipolar disorder. In addition, fewer studies have explored the possibility that altered brain metabolism may be associated with suicide attempt. To begin to fill in these gaps, we evaluated functional (task based fMRI) and metabolic (quantitative T1ρ) differences associated with suicide attempt in participants with bipolar disorder. Thirty-nine participants with bipolar disorder underwent fMRI during a flashing checkerboard task and 27 also underwent quantitative T1ρ. The relationship between neuroimaging and history of suicide attempt was tested using multiple regression while adjusting for age, sex, and current mood state. Differences between two measures of suicide attempt (binary: yes/no and continuous: number of attempts) were quantified using the corrected Akaike Information Criterion. Participants who had attempted suicide had greater fMRI task-related activation in visual areas and the cerebellum. The number of suicide attempts was associated with a difference in BOLD response in the amygdala, prefrontal cortex, and cerebellum. Increased quantitative T1ρ was associated with number of suicide attempts in limbic, basal ganglia, and prefrontal cortex regions. This study is a secondary analysis with a modest sample size. Differences between measures of suicide history may be due to differences in statistical power. History of suicide was associated with limbic, prefrontal, and cerebellar alterations. Results comparing those with and without suicide attempts differed from results using number of suicide attempts, suggesting that these variables have different neurobiological underpinnings.

A Computational Model of Hopelessness and Active-Escape Bias in Suicidality

Currently, psychiatric practice lacks reliable predictive tools and a sufficiently detailed mechanistic understanding of suicidal thoughts and behaviors (STB) to provide timely and personalized interventions. Developing computational models of STB that integrate across behavioral, cognitive and neural levels of analysis could help better understand STB vulnerabilities and guide personalized interventions. To that end, we present a computational model based on the active inference framework. With this model, we show that several STB risk markers - hopelessness, Pavlovian bias and active-escape bias - are interrelated via the drive to maximize one's model evidence. We propose four ways in which these effects can arise: (1) increased learning from aversive outcomes, (2) reduced belief decay in response to unexpected outcomes, (3) increased stress sensitivity and (4) reduced sense of stressor controllability. These proposals stem from considering the neurocircuits implicated in STB: how the locus coeruleus - norepinephrine (LC-NE) system together with the amygdala (Amy), the dorsal prefrontal cortex (dPFC) and the anterior cingulate cortex (ACC) mediate learning in response to acute stress and volatility as well as how the dorsal raphe nucleus - serotonin (DRN-5-HT) system together with the ventromedial prefrontal cortex (vmPFC) mediate stress reactivity based on perceived stressor controllability. We validate the model by simulating performance in an Avoid/Escape Go/No-Go task replicating recent behavioral findings. This serves as a proof of concept and provides a computational hypothesis space that can be tested empirically and be used to distinguish planful versus impulsive STB subtypes. We discuss the relevance of the proposed model for treatment response prediction, including pharmacotherapy and psychotherapy, as well as sex differences as it relates to stress reactivity and suicide risk.

Spontaneous transient states of fronto-temporal and default-mode networks altered by suicide attempt in major depressive disorder

Major depressive disorder (MDD) is associated with increased suicidality, and it's still challenging to identify suicide in clinical practice. Although suicide attempt (SA) is the most relevant precursor with multiple functional abnormalities reported from neuroimaging studies, little is known about how the spontaneous transient activated patterns organize and coordinate brain networks underlying SA. Thus, we obtained resting-state magnetoencephalography data for two MDD subgroups of 44 non-suicide patients and 34 suicide-attempted patients, together with 49 matched health-controls. For the source-space signals, Hidden Markov Model (HMM) helped to capture the sub-second dynamic activity via a hidden sequence of finite number of states. Temporal parameters and spectral activation were acquired for each state and then compared between groups. Here, HMM states characterized the spatiotemporal signatures of eight networks. The activity of suicide attempters switches more frequently into the fronto-temporal network, as the time spent occupancy of fronto-temporal state is increased and interval time is decreased compared with the non-suicide patients. Moreover, these changes are significantly correlated with Nurses' Global Assessment of Suicide Risk scores. Suicide attempters also exhibit increased state-wise activations in the theta band (4-8 Hz) in the posterior default mode network centered on posterior cingulate cortex, which can't be detected in the static spectral analysis. These alternations may disturb the time allocations of cognitive control regulations and cause inflexible decision making to SA. As the better sensitivity of dynamic study in reflecting SA diathesis than the static is validated, dynamic stability could serve as a potential neuronal marker for SA.

Abnormal degree centrality in first-episode medication-free adolescent depression at rest: A functional magnetic resonance imaging study and support vector machine analysis

BACKGROUND

Depression in adolescents is more heterogeneous and less often diagnosed than depression in adults. At present, reliable approaches to differentiating between adolescents who are and are not affected by depression are lacking. This study was designed to assess voxel-level whole-brain functional connectivity changes associated with adolescent depression in an effort to define an imaging-based biomarker associated with this condition.

MATERIALS AND METHODS

In total, 71 adolescents affected by major depressive disorder (MDD) and 71 age-, sex-, and education level-matched healthy controls were subjected to resting-state functional magnetic resonance imaging (rs-fMRI) based analyses of brain voxel-wise degree centrality (DC), with a support vector machine (SVM) being used for pattern classification analyses.

RESULTS

DC patterns derived from 16-min rs-fMRI analyses were able to effectively differentiate between adolescent MDD patients and healthy controls with 95.1% accuracy (136/143), and with respective sensitivity and specificity values of 92.1% (70/76) and 98.5% (66/67) based upon DC abnormalities detected in the right cerebellum. Specifically, increased DC was evident in the bilateral insula and left lingual area of MDD patients, together with reductions in the DC values in the right cerebellum and bilateral superior parietal lobe. DC values were not significantly correlated with disease severity or duration in these patients following correction for multiple comparisons.

CONCLUSION

These results suggest that whole-brain network centrality abnormalities may be present in many brain regions in adolescent depression patients. Accordingly, these DC maps may hold value as candidate neuroimaging biomarkers capable of differentiating between adolescents who are and are not affected by MDD, although further validation of these results will be critical.

Structural covariance pattern abnormalities of insula in major depressive disorder: A CAN-BIND study report

BACKGROUND AND METHODS

Investigation of the insula may inform understanding of the etiopathogenesis of major depressive disorder (MDD). In the present study, we introduced a novel gray matter volume (GMV) based structural covariance technique, and applied it to a multi-centre study of insular subregions of 157 patients with MDD and 93 healthy controls from the Canadian Biomarker Integration Network in Depression (CAN-BIND, https://www.canbind.ca/). Specifically, we divided the unilateral insula into three subregions, and investigated their coupling with whole-brain GMV-based structural brain networks (SBNs). We compared between-group difference of the structural coupling patterns between the insular subregions and SBNs.

RESULTS

The insula was divided into three subregions, including an anterior one, a superior-posterior one and an inferior-posterior one. In the comparison between MDD patients and controls we found that patients' right anterior insula showed increased inter-network coupling with the default mode network, and it showed decreased inter-network coupling with the central executive network; whereas patients' right ventral-posterior insula showed decreased inter-network coupling with the default mode network, and it showed increased inter-network coupling with the central executive network. We also demonstrated that patients' loading parameters of the right ventral-posterior insular structural covariance negatively correlated with their suicidal ideation scores; and controls' loading parameters of the right ventral-posterior insular structural covariance positively correlated with their motor and psychomotor speed scores, whereas these phenomena were not found in patients. Additionally, we did not find significant inter-network coupling between the whole-brain SBNs, including salience network, default mode network, and central executive network.

CONCLUSIONS

Our work proposed a novel technique to investigate the structural covariance coupling between large-scale structural covariance networks, and provided further evidence that MDD is a system-level disorder that shows disrupted structural coupling between brain networks.

Effects of polygenic risk for suicide attempt and risky behavior on brain structure in young people with familial risk of bipolar disorder

Bipolar disorder (BD) is associated with a 20-30-fold increased suicide risk compared to the general population. First-degree relatives of BD patients show inflated rates of psychopathology including suicidal behaviors. As reliable biomarkers of suicide attempts (SA) are lacking, we examined associations between suicide-related polygenic risk scores (PRSs)-a quantitative index of genomic risk-and variability in brain structures implicated in SA. Participants (n = 206; aged 12-30 years) were unrelated individuals of European ancestry and comprised three groups: 41 BD cases, 96 BD relatives ("high risk"), and 69 controls. Genotyping employed PsychArray, followed by imputation. Three PRSs were computed using genome-wide association data for SA in BD (SA-in-BD), SA in major depressive disorder (SA-in-MDD) (Mullins et al., 2019, The American Journal of Psychiatry, 176(8), 651-660), and risky behavior (Karlsson Linnér et al., 2019, Nature Genetics, 51(2), 245-257). Structural magnetic resonance imaging processing employed FreeSurfer v5.3.0. General linear models were constructed using 32 regions-of-interest identified from suicide neuroimaging literature, with false-discovery-rate correction. SA-in-MDD and SA-in-BD PRSs negatively predicted parahippocampal thickness, with the latter association modified by group membership. SA-in-BD and Risky Behavior PRSs inversely predicted rostral and caudal anterior cingulate structure, respectively, with the latter effect driven by the "high risk" group. SA-in-MDD and SA-in-BD PRSs positively predicted cuneus structure, irrespective of group. This study demonstrated associations between PRSs for suicide-related phenotypes and structural variability in brain regions implicated in SA. Future exploration of extended PRSs, in conjunction with a range of biological, phenotypic, environmental, and experiential data in high risk populations, may inform predictive models for suicidal behaviors.

Insomnia symptom severity is associated with increased suicidality and death by suicide in a sample of patients with psychiatric disorders

STUDY OBJECTIVES

Insomnia is a risk factor for suicidal behavior including attempts and death by suicide. We investigated whether insomnia symptom severity was associated with suicidality and death by suicide in patients with psychiatric disorders.

METHODS

The sample included 180 deceased patients with psychiatric disorders seen at Weber Human Services between 2008 and 2018 who completed the Outpatient Questionnaire-45.2 (OQ) prior to death. Insomnia symptom severity was assessed using item 41 from the OQ. Manner of death was determined by death records and autopsy reports. History of suicidality was determined through electronic medical records. Cases were grouped into four lifetime categories: non-suicidal (n = 30), suicidal ideation (n = 36), suicide attempt (n = 95), and death by suicide (n = 19). Demographic, medical, and psychiatric features of each group were compared using linear regression. Logistic regression was used to determine whether insomnia symptom severity was associated with lifetime suicidality severity grouping, adjusting for psychiatric disorders commonly linked to suicidality.

RESULTS

Lifetime suicidality was associated with sleep problems, fatigue, headaches, and psychiatric disorders (i.e. depressive, personality, and trauma-related disorders). Referenced to the non-suicidal group, greater insomnia symptom severity was significantly associated with suicide attempts and death by suicide, with odds ratios (OR) of OR = 2.67, p = 0.011, and OR = 5.53, p = 0.002, respectively, even after adjusting important psychiatric diagnoses.

CONCLUSIONS

Results suggest that insomnia symptom severity endorsed during a clinical visit is associated with heightened suicidality, especially suicidal behavior. The presence of insomnia symptoms in patients with psychiatric disorders may indicate risk for suicide and is a target for suicide prevention.

Anomalous Amygdala Habituation to Unpleasant Stimuli Among Unmedicated Individuals With Borderline Personality Disorder and a History of Self-Harming Behavior

Self-harming behavior (SB) is one of the diagnostic criteria for borderline personality disorder (BPD). However, it is not exhibited by all individuals with BPD. Furthermore, studies examining the neural correlates of SB in BPD are lacking. Given research showing that BPD patients have difficulty habituating to affective stimuli, this study investigated whether anomalous amygdala activation is specific to BPD patients with SB. The authors used fMRI to compare amygdala activation in BPD patients with SB (n = 15) to BPD patients without SB (n = 18) and healthy controls (n = 32) during a task involving pleasant, neutral, and unpleasant pictures, presented twice. BPD patients with SB demonstrated greater amygdala activity during the second presentation of unpleasant pictures. Results highlight neurobiological differences in BPD patients with and without SB and suggest that anomalous amygdala habituation to unpleasant stimuli may be related to SB.

Characteristics of Intrinsic Brain Functional Connectivity Alterations in Major Depressive Disorder Patients With Suicide Behavior

BACKGROUND

The intrinsic brain functional connectivity of suicide attempts in major depressive disorder (MDD) remains incompletely understood.

PURPOSE

To investigate graph-theoretical based functional connectivity strength (FCS) alterations in MDD patients with suicidal behavior.

STUDY TYPE

Prospective.

SUBJECTS

Fifty medication-free MDD patients, with (suicide attempters, SA, N = 15) and without (non-attempters, nSA, N = 35) a history of a suicide attempt, and 37 healthy controls (HC).

FIELD STRENGTH/SEQUENCE

Resting-state functional magnetic resonance imaging (fMRI) using a gradient-echo imaging sequence was acquired at 3.0 T.

ASSESSMENT

For each individual, voxel-wise whole-brain functional network was constructed and graph-theoretical based FCS map was calculated. For each individual in two patient groups, the seed-based functional connectivity map was constructed.

STATISTICAL TESTS

Non-parameter permutation tests, analysis of covariance, two-sample t-test, Chi-square test, and Pearson correlation analysis. A P value <0.05 was considered statistically significant.

RESULTS

Relative to the HC group, two MDD patient groups showed significantly lower FCS in the left hippocampus, while nSA patients showed additionally lower FCS in more widespread regions (P < 0.05). Importantly, comparing to nSA patients, SA patients had significantly higher FCS in the right orbitofrontal cortex (OFC) and bilateral dorsomedial prefrontal cortex (dmPFC) (P < 0.05). Further seed-based functional connectivity analysis revealed that the right OFC exhibited significantly higher connectivity to right middle frontal gyrus and lower connectivity to the left anterior cingulate cortex and left calcarine sulcus, and the bilateral dmPFC had significantly higher connectivity to the left middle frontal gyrus and right inferior temporal gyrus in the SA patients than in the nSA patients (P < 0.05).

DATA CONCLUSION

This study identified disconnections of the OFC and dmPFC which were putatively related to a higher risk of suicidal behavior in MDD patients, thus extended the understanding of suicidal behavior at a brain circuit level.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 3.

Quantum and Electromagnetic Fields in Our Universe and Brain: A New Perspective to Comprehend Brain Function

The concept of wholeness or oneness refers to not only humans, but also all of creation. Similarly, consciousness may not wholly exist inside the human brain. One consciousness could permeate the whole universe as limitless energy; thus, human consciousness can be regarded as limited or partial in character. According to the limited consciousness concept, humans perceive projected waves or wave-vortices as a waveless item. Therefore, human limited consciousness collapses the wave function or energy of particles; accordingly, we are only able to perceive them as particles. With this “limited concept”, the wave-vortex or wave movement comes into review, which also seems to have a limited concept, i.e., the limited projected wave concept. Notably, this wave-vortex seems to embrace photonic light, as well as electricity and anything in between them, which gives a sense of dimension to our brain. These elements of limited projected wave-vortex and limitless energy (consciousness) may coexist inside our brain as electric (directional pilot wave) and quantum (diffused oneness of waves) brainwaves, respectively, with both of them giving rise to one brain field. Abnormality in either the electrical or the quantum field or their fusion may lead to abnormal brain function.

Structural brain correlates of irritability and aggression in early manifest Huntington's disease

In Huntington's disease (HD), irritability and aggressive behavior represent highly prevalent and disabling neuropsychiatric symptoms. However, their structural brain correlates have not been extensively explored. Here, we rated the severity of irritability and aggression (IAs) using the Problem Behaviors Assessment for HD (PBA-s) in 31 early HD participants. The IAs score was computed as the mean severity score for the irritability plus the mean severity aggression PBA-s items. Seventeen patients were classified as IAs (IAs score > 2) and 14 as non-IAs. All participants had available T1-MRI data. A grey matter volume voxel-based morphometry group comparison was performed, using age, motor status, severity of other PBA-s items and disease burden as covariates. Aside from irritability, aggression and obsessive-compulsive behavior, both groups were comparable in terms of other clinical and sociodemographic variables. In the IAs group, a significant reduction of grey-matter volume (GMV) was found in the bilateral caudate, putamen and globus pallidus, left pulvinar nucleus, right superior temporal pole (BA 38), left mid temporal gyrus (BA 21), right inferior temporal gyrus (BA 20) and left medial OPFC (BA 11). Lower GMV in the left pulvinar nucleus was significantly associated with higher anxiety and lower GMV in the left medial OPFC was significantly associated with higher suicidality. In sum, IAs in HD is associated with structural brain damage in a set of key nodes involved in the expression and down-regulation of negative emotions.

Atrophy of right inferior frontal orbital gyrus and frontoparietal functional connectivity abnormality in depressed suicide attempters

Although structural and functional brain abnormalities have been observed in depressed suicide attempters (DS), structural deficits and functional impairments together with their relationship in DS remain unclear. To clarify this issue, we aimed to examine the differences in gray matter (GM) alteration, corresponding functional connectivity (FC) change, and their relationship between DS and depressed non-suicide attempters (NDS). Sixty-eight DS, 119 NDS and 103 healthy controls were enrolled and subjected to magnetic resonance imaging scans. The patients were evaluated using the 17-item Hamilton Rating Scale for Depression (HRSD) and Nurses' Global Assessment of Suicide Risk (NGASR) scale. Both voxel-based morphometry and resting-state FC analyses were performed based on functional and structural imaging data. Compared with NDS, the DS group showed reduced GM volume in the right inferior frontal orbital gyrus (IFOG) and left caudate (CAU) but increased GM volume in the left calcarine fissure, weaker negative right IFOG-left rectus gyrus (REG) FC, and weaker positive right IFOG-left inferior parietal lobule (IPL) FC. In DS, the GM volume of the right IFOG and left CAU was negatively correlated with NGASR and HRSD scores, respectively; the right IFOG-left IPL FC was negatively correlated with cognitive factor scores; and the GM volume of the right IFOG was positively correlated with IFOG-REG and IFOG-IPL FC. Our findings indicate that structural deficit with its related functional alterations in brain circuits converged in right IFOG centralized pathways and may play a central role in suicidal behaviors in depression.

The processing of angry faces in schizophrenia patients with a history of suicide: An fMRI study examining brain activity and connectivity

BACKGROUND

The high rate of suicidal behaviours (SBs) in psychiatric populations remain an important preoccupation to address. The literature reveals emotional instability as an important risk factor for SBs. However, the neural mechanisms underpinning this risk factor have never been investigated in schizophrenia patients with SBs. The following study implemented a task-based emotional processing functional magnetic resonance imaging (fMRI) paradigm to evaluate the activation and connectivity differences exhibited by schizophrenia patients with a history of suicide attempt (SA).

METHOD

A sample of 62 schizophrenia patients with and without SA and 22 controls completed an fMRI emotional processing task, which included the visualization of dynamic angry facial expressions. Task-based connectivity was assessed using generalized psychophysical interaction analyses.

RESULTS

During the processing of angry faces, suicidal schizophrenia patients displayed increased activation of the left median cingulate gyrus, left middle frontal gyrus, and left precuneus when compared to nonsuicidal schizophrenia patients and healthy controls. Whole-brain connectivity analyses yielded an increased coupling of the right amygdala and right superior frontal gyrus, as well as between the left precuneus and median cingulate gyrus, in suicidal schizophrenia patients. Schizophrenia patients' hostility scores on the Positive and Negative Symptom Scale (PANSS) were significantly and positively correlated with the activity of the left median cingulate gyrus.

CONCLUSION

When exposed to angry faces, suicidal schizophrenia patients demonstrate elevated activation of brain regions associated to executive functioning and self-processing, as well as aberrant fronto-limbic connectivity involved in emotion regulation. Our results highlight the neglected role of anger when investigating the neural alterations underpinning SBs in schizophrenia.

Reasoning, problem solving, attention/vigilance, and working memory are candidate phenotypes of non-suicidal self-injury in Chinese Han nationality

BACKGROUND

Non-suicidal self-injury (NSSI) is an act of deliberately hurting one's body without the purpose of death. Internal phenotypes have been used in numerous studies of mental disorders, suicide, and self-injury. This research aimed to evaluate the cognitive function of patients with NSSI and determine their potential endophenotype.

METHODS

This study used a comparative control design and included 61 patients with NSSI, 55 healthy siblings (HS), and 53 healthy controls. Visual learning, reasoning and problem, verbal learning, attention/vigilance, working memory, and speed of processing were used to evaluate the cognitive function of the subjects.

RESULTS

Patients with NSSI and their HS showed cognitive defects in reasoning and problem, attention/vigilance, and working memory. Substantial differences were observed in verbal learning among the three groups, but no significant difference was recorded in the scores in Brief Assessment of Cognition in Schizophrenia.

CONCLUSIONS

The results suggest that reasoning and problem, attention/vigilance, and working memory may be potential endophenotypes in early identification of Chinese Han people with NSSI behavior.

Volumetric MRI Analysis of Brain Structures in Patients with History of First and Repeated Suicide Attempts: A Cross Sectional Study

Structural brain changes are found in suicide attempters and in patients with mental disorders. It remains unclear whether the suicidal behaviors are related to atrophy of brain regions and how the morphology of specific brain areas is changing with each suicide attempt. The sample consisted of 56 patients hospitalized after first suicide attempt (first SA) (n = 29), more than one suicide attempt (SA > 1) (n = 27) and 54 healthy controls (HC). Brain volume was measured using FreeSurfer 6.0 automatic segmentation technique. In comparison to HC, patients with first SA had significantly lower cortical thickness of the superior and rostral middle frontal areas, the inferior, middle and superior temporal areas of the left hemisphere and superior frontal area of the right hemisphere. In comparison to HC, patients after SA > 1 had a significantly lower cortical thickness in ten areas of frontal cortex of the left hemisphere and seven areas of the right hemisphere. The comparison of hippocampus volume showed a significantly lower mean volume of left and right parts in patients with SA > 1, but not in patients with first SA. The atrophy of frontal, temporal cortex and hippocampus parts was significantly higher in repeated suicide attempters than in patients with first suicide attempt.

Temporal dynamics alterations of spontaneous neuronal activity in anterior cingulate cortex predict suicidal risk in bipolar II patients

Bipolar disorder type II (BD-II) is linked to an increased suicidal risk. Since a prior suicide attempt (SA) is the single most important risk factor for sequent suicide, the elucidation of involved neural substrates is critical for its prevention. Therefore, we examined the spontaneous brain activity and its temporal variabilities in suicide attempters with bipolar II during a major depressive episode. In this cross-sectional study, 101 patients with BD-II, including 44 suicidal attempters and 57 non-attempters, and 60 non-psychiatric controls underwent a resting-state functional magnetic resonance imaging (fMRI). Participants were assessed with Hamilton Rating Scale for Depression (HAMD) and Nurses^, Global Assessment of Suicide Risk (NGASR). The dynamics of low-frequency fluctuation (dALFF) was measured using sliding-window analysis and its correlation with suicidal risk was conducted using Pearson correlation. Compared to non-attempters, suicidal attempters showed an increase in brain activity and temporal dynamics in the anterior cingulate cortex (ACC). In addition, the temporal variabilities of ACC activity positively correlated with suicidal risk (R = 0.45, p = 0.004), while static ACC activity failed to (R = 0.08, p > 0.05). Our findings showed that an aberrant static ALFF and temporal variability could affect suicidal behavior in BD-II patients. However, temporal variability of neuronal activity was more sensitive than static amplitude in reflecting diathesis for suicide in BD-II. Dynamics of brain activity could be considered in developing neuromarkers for suicide prevention.

Altered cortical morphology in major depression disorder patients with suicidality

Background

Major depressive disorder (MDD) is associated with high risk of suicide, but the biological underpinnings of suicidality in MDD patients are far from conclusive. Previous neuroimaging studies using voxel-based morphometry (VBM) demonstrated that depressed individuals with suicidal thoughts or behaviors exhibit specific cortical structure alterations. To complement VBM findings, surface-based morphometry (SBM) can provide more details into gray matter structure, including the cortical complexity, cortical thickness and sulcal depth for brain images.

Objective

This study aims to use SBM to investigate cortical morphology alterations to obtain evidence for neuroanatomical alterations in depressed patients with suicidality.

Methods

Here, 3D T1-weighted MR images of brain from 39 healthy controls, 40 depressed patients without suicidality (patient controls), and 39 with suicidality (suicidal groups) were analyzed based on SBM to estimate the fractal dimension, gyrification index, sulcal depth, and cortical thickness using the Computational Anatomy Toolbox. Correlation analyses were performed between clinical data and cortical surface measurements from patients.

Results

Surface-based morphometry showed decreased sulcal depth in the parietal, frontal, limbic, occipital and temporal regions and decreased fractal dimension in the frontal regions in depressed patients with suicidality compared to both healthy and patient controls. Additionally, in patients with depression, the sulcal depth of the left caudal anterior cingulate cortex was negatively correlated with Hamilton Depression Rating Scale scores.

Conclusions

Depressed patients with suicidality had abnormal cortical morphology in some brain regions within the default mode network, frontolimbic circuitry and temporal regions. These structural deficits may be associated with the dysfunction of emotional processing and impulsivity control. This study provides insights into the underlying neurobiology of the suicidal brain.

Common and Specific Alterations of Amygdala Subregions in Major Depressive Disorder With and Without Anxiety: A Combined Structural and Resting-State Functional MRI Study

Anxious major depressive disorder is a common subtype of major depressive disorder; however, its unique neural mechanism is not well-understood currently. Using multimodal MRI data, this study examined common and specific alterations of amygdala subregions between patients with and without anxiety. No alterations were observed in the gray matter volume or intra-region functional integration in either patient group. Compared with the controls, both patient groups showed decreased functional connectivity between the left superficial amygdala and the left putamen, and between the right superficial amygdala and the bilateral anterior cingulate cortex and medial orbitofrontal cortex, while only patients with anxiety exhibited decreased activity in the bilateral laterobasal and superficial amygdala. Moreover, the decreased activity correlated negatively with the Hamilton depression scale scores in the patients with anxiety. These findings provided insights into the pathophysiologic processes of anxious major depressive disorder and may help to develop new and effective treatment programs.

Identification of suicidality in adolescent major depressive disorder patients using sMRI: A machine learning approach

BACKGROUND

Suicidal behavior is a major concern for patients who suffer from major depressive disorder (MDD), especially among adolescents and young adults. Machine learning models with the capability of suicide risk identification at an individual level could improve suicide prevention among high-risk patient population.

METHODS

A cross-sectional assessment was conducted on a sample of 66 adolescents/young adults diagnosed with MDD. The structural T1-weighted MRI scan of each subject was processed using the FreeSurfer software. The classification model was conducted using the Support Vector Machine - Recursive Feature Elimination (SVM-RFE) algorithm to distinguish suicide attempters and patients with suicidal ideation but without attempts.

RESULTS

The SVM model was able to correctly identify suicide attempters and patients with suicidal ideation but without attempts with a cross-validated prediction balanced accuracy of 78.59%, the sensitivity was 73.17% and the specificity was 84.0%. The positive predictive value of suicide attempt was 88.24%, and the negative predictive value was 65.63%. Right lateral orbitofrontal thickness, left caudal anterior cingulate thickness, left fusiform thickness, left temporal pole volume, right rostral anterior cingulate volume, left lateral orbitofrontal thickness, left posterior cingulate thickness, right pars orbitalis thickness, right posterior cingulate thickness, and left medial orbitofrontal thickness were the 10 top-ranked classifiers for suicide attempt.

CONCLUSIONS

The findings indicated that structural MRI data can be useful for the classification of suicide risk. The algorithm developed in current study may lead to identify suicide attempt risk among MDD patients.

Alterations in gray matter volumes and intrinsic activity in the prefrontal cortex are associated with suicide attempts in patients with bipolar disorder

Bipolar disorder (BD) is associated with increased suicidal behavior. Understanding the neural features of suicide attempts (SA) in patients with BD is critical to preventing suicidal behavior. The prefrontal cortex (PFC) is a key region related to SA. In this study, forty BD patients with a history of SA (BD+SA), 70 BD patients without a history of SA (BD-SA), and 110 individuals in a healthy control (HC) group underwent structural magnetic resonance imaging (MRI) and resting-state functional MRI. We used voxel-based morphometry (VBM) and amplitude of low frequency fluctuations (ALFF) techniques to examine the gray matter volumes (GMVs) and ALFF values in the PFC. Compared with the HC group, both the BD+SA and BD-SA groups had lower GMVs and higher ALFF values in the medial PFC (MPFC), ventral PFC (VPFC), and dorsolateral PFC (DLPFC). The ALFF values in the MPFC, VPFC, and DLPFC in the BD+SA group were significantly higher than those in the BD-SA group. These findings suggest that BD patients with SA have intrinsic activity abnormalities in PFC regions. This provides potentially identifiable neuroimaging markers in BD patients with SA that could be used to increase our understanding of suicidal behavior.

Examination of structural brain changes in recent suicidal behavior

We aimed to identify brain structural changes in cortical and subcortical regions linked to recent suicidal behavior. We performed secondary analyses of structural MRI data of two independent studies, namely the Establishing Moderators/Biosignatures of Antidepressant Response - Clinical Care (EMBARC) study and a Little Rock study on acute suicidal behavior. Study 1 (EMBARC, N = 187), compared individuals with remote suicide attempts (Remote-SA), individuals with lifetime suicide ideation but no attempts (Lifetime-SI only), and depressed individuals without lifetime suicide ideation or attempts (non-suicidal depressed). Study 2 (Little Rock data, N = 34) included patients recently hospitalized for suicide ideation or attempt constituted by: patients who recently attempted suicide (Recent-SA), individuals with remote suicide attempts (Remote-SA), and Lifetime-SI only. Study 3 combined the EMBARC and Little Rock datasets including Recent-SA, Remote-SA, Lifetime-SI only and non-suicidal depressed individuals. In Study 1 and Study 2, no significant differences were observed between groups. In Study 3, significantly lower middle temporal gyrus thickness, insular surface area, and thalamic volume and higher volume in the nucleus accumbens were observed in Recent-SA. This pattern of structural abnormalities may underlie pain and emotion dysregulation, which have been linked to the transition from suicidal thoughts to action.

Increased Amygdala-Paracentral Lobule/Precuneus Functional Connectivity Associated With Patients With Mood Disorder and Suicidal Behavior

Mood disorder patients have greater suicide risk than members of the general population, but how suicidal behavior relates to brain functions has not been fully elucidated. This study investigated how functional connectivity (FC) values between the right/left amygdala and the whole brain relate to suicidal behavior in patients with mood disorder. The participants in this study were 100 mood disorder patients with suicidal behavior (SB group), 120 mood disorder patients with non-suicidal behavior (NSB group), and 138 age- and gender-matched healthy controls (HC group). Whole-brain FC values among the three groups were compared using an analysis of covariance (ANCOVA). Compared to the NSB and HC groups, increased FC values in the right amygdala-bilateral paracentral lobule/precuneus circuit were observed in the SB group (Bonferroni-corrected, p < 0.017). The FC values in the NSB group did not differ significantly from those in the HC group (Bonferroni-corrected, p > 0.017). Moreover, there were no significant differences in FC values between mood disorder patients with suicide attempt (SA group) and mood disorder patients with suicidal ideation (SI group), while the FC values between the right amygdala and bilateral paracentral lobule/precuneus in the SA group were higher than the mean in the SI group. These findings suggest that right amygdala-paracentral lobule/precuneus dysfunction has an important role in patients with mood disorder and suicidal behavior.