Differences in brain surface area and cortical volume between suicide attempters and non-attempters with major depressive disorder

Whole-brain structural and functional neuroimaging of individuals who attempted suicide and people who did not: A systematic review and exploratory coordinate-based meta-analysis

Suicide is the cause of death of approximately 800,000 people a year. Despite the relevance of this behaviour, risk assessment tools rely on clinician experience and subjective ratings. Given that previous suicide attempts are the single strongest predictors of future attempts, we designed a systematic review and coordinate-based meta-analysis to demonstrate whether neuroimaging features can help distinguish individuals who attempted suicide from subjects who did not. Out of 5,659 publications from PubMed, Scopus, and Web of Science, we summarised 102 experiments and meta-analysed 23 of them. A cluster in the right superior temporal gyrus, a region implicated in emotional processing, might be functionally hyperactive in individuals who attempted suicide. No statistically significant differences in brain morphometry were evidenced. Furthermore, we used JuSpace to show that this cluster is enriched in 5-HT1A heteroreceptors in the general population. This exploratory meta-analysis provides a putative neural substrate linked to previous suicide attempts. Heterogeneity in the analytical techniques and weak or absent power analysis of the studies included in this review currently limit the applicability of the findings, the replication of which should be prioritised.

Abnormalities in brain structure following childhood unpredictability: a mechanism underlying depressive and anxiety symptoms

BACKGROUND

Childhood adversity is associated with abnormalities in brain structure, but this association has not been tested for childhood unpredictability, one form of adversity. We studied whether abnormalities in gray matter volume (GMV) could be a mechanism linking childhood unpredictability and psychopathology, over and above the effect of childhood trauma.

METHODS

Participants were 158 right-handed healthy young adults (aged 17-28 years, M = 22.07, s.d. = 2.08; 66.46% female) who underwent structural magnetic resonance imaging measurements and provided retrospective reports of childhood unpredictability. The anxiety and depression subscales of the self-report Brief Symptom Inventory-53 were used to index psychopathology.

RESULTS

Whole-brain voxel-based morphometric analyses showed that after controlling for the effect of childhood trauma, childhood unpredictability was correlated with greater GMV in bilateral frontal pole, bilateral precuneus, bilateral postcentral gyrus, right hemisphere of fusiform, and lingual gyrus, and left hemisphere of ventrolateral prefrontal cortex as well as occipital gyrus. Greater GMV in bilateral frontal pole, bilateral precuneus, and bilateral postcentral gyrus mediated associations between unpredictability and symptoms of depression and anxiety.

CONCLUSIONS

The findings suggest that childhood unpredictability could exact unique effects on neural development, over and above the effect of childhood trauma. These findings are relevant for understanding the occurrence of psychopathology following childhood unpredictability and have implications for intervention.

A multimodal prediction model for suicidal attempter in major depressive disorder

Background

Suicidal attempts in patients with major depressive disorder (MDD) have become an important challenge in global mental health affairs. To correctly distinguish MDD patients with and without suicidal attempts, a multimodal prediction model was developed in this study using multimodality data, including demographic, depressive symptoms, and brain structural imaging data. This model will be very helpful in the early intervention of MDD patients with suicidal attempts.

Methods

Two feature selection methods, support vector machine-recursive feature elimination (SVM-RFE) and random forest (RF) algorithms, were merged for feature selection in 208 MDD patients. SVM was then used as a classification model to distinguish MDD patients with suicidal attempts or not.

Results

The multimodal predictive model was found to correctly distinguish MDD patients with and without suicidal attempts using integrated features derived from SVM-RFE and RF, with a balanced accuracy of 77.78%, sensitivity of 83.33%, specificity of 70.37%, positive predictive value of 78.95%, and negative predictive value of 76.00%. The strategy of merging the features from two selection methods outperformed traditional methods in the prediction of suicidal attempts in MDD patients, with hippocampal volume, cerebellar vermis volume, and supracalcarine volume being the top three features in the prediction model.

Conclusions

This study not only developed a new multimodal prediction model but also found three important brain structural phenotypes for the prediction of suicidal attempters in MDD patients. This prediction model is a powerful tool for early intervention in MDD patients, which offers neuroimaging biomarker targets for treatment in MDD patients with suicidal attempts.

Sex differences of brain cortical structure in major depressive disorder

Background

Major depressive disorder (MDD) has different clinical presentations in males and females. However, the neuroanatomical mechanisms underlying these sex differences are not fully understood.

Objective

The purpose of present study was to explore the sex differences in brain cortical thickness (CT) and surface area (SA) of MDD and the relationship between these differences and clinical manifestations in different gender.

Methods

High-resolution T1-weighted images were acquired from 61 patients with MDD and 61 healthy controls (36 females and 25 males, both). The sex differences in CT and SA were obtained using the FreeSurfer software and compared between every two groups by post hoc test. Spearman correlation analysis was also performed to explore the relationships between these regions and clinical characteristics.

Results

In male patients with MDD, the CT of the right precentral was thinner compared to female patients, although this did not survive Bonferroni correction. The SA of several regions, including right superior frontal, medial orbitofrontal gyrus, inferior frontal gyrus triangle, superior temporal, middle temporal, lateral occipital gyrus, and inferior parietal lobule in female patients with MDD was smaller than that in male patients (P < 0.01 after Bonferroni correction). In female patients, the SA of the right superior temporal (r = 0.438, P = 0.008), middle temporal (r = 0.340, P = 0.043), and lateral occipital gyrus (r = 0.372, P = 0.025) were positively correlated with illness duration.

Conclusion

The current study provides evidence of sex differences in CT and SA in patients with MDD, which may improve our understanding of the sex-specific neuroanatomical changes in the development of MDD.

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

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

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.

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

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

Aberrant dynamic functional connectivity in corticostriatal circuitry in depressed bipolar II disorder with recent suicide attempt

BACKGROUND

The underlying neurobiological mechanisms on suicidal behavior in bipolar disorder remain unclear. We aim to explore the mechanisms of suicide by detecting dynamic functional connectivity (dFC) of corticostriatal circuitry and cognition in depressed bipolar II disorder (BD II) with recent suicide attempt (SA).

METHODS

We analyzed resting-state functional magnetic resonance imaging (fMRI) data from 68 depressed patients with BD-II (30 with SA and 38 without SA) and 35 healthy controls (HCs). The whole-brain dFC variability of corticostriatal circuitry was calculated using a sliding-window analysis. Their correlations with cognitive dysfunction were further detected. Support vector machine (SVM) classification tested the potential of dFC to differentiate BD-II with SA from HCs.

RESULTS

Increased dFC variability between the right vCa and the right insula was found in SA compared to non-SA and HCs, and negatively correlated with speed of processing. Decreased dFC variability between the left dlPu and the right postcentral gyrus was found in non-SA compared to SA and HCs, and positively correlated with reasoning problem-solving. Both SA and non-SA exhibited decreased dFC variability between the right dCa and the left MTG, and between the right dlPu and the right calcarine when compared to HCs. SVM classification achieved an accuracy of 75.24 % and AUC of 0.835 to differentiate SA from non-SA, while combining the abnormal dFC features between SA and non-SA.

CONCLUSIONS

Aberrant dFC variability of corticostriatal circuitry may serve as potential neuromarker for SA in BD-II, which might help to discriminate suicidal BD-II patients from non-suicidal patients and HCs.

Clinical MRI morphological analysis of functional seizures compared to seizure-naïve and psychiatric controls

PURPOSE

Functional seizures (FS), also known as psychogenic nonepileptic seizures (PNES), are physical manifestations of acute or chronic psychological distress. Functional and structural neuroimaging have identified objective signs of this disorder. We evaluated whether magnetic resonance imaging (MRI) morphometry differed between patients with FS and clinically relevant comparison populations.

METHODS

Quality-screened clinical-grade MRIs were acquired from 666 patients from 2006 to 2020. Morphometric features were quantified with FreeSurfer v6. Mixed-effects linear regression compared the volume, thickness, and surface area within 201 regions-of-interest for 90 patients with FS, compared to seizure-naïve patients with depression (n = 243), anxiety (n = 68), and obsessive-compulsive disorder (OCD, n = 41), respectively, and to other seizure-naïve controls with similar quality MRIs, accounting for the influence of multiple confounds including depression and anxiety based on chart review. These comparison populations were obtained through review of clinical records plus research studies obtained on similar scanners.

RESULTS

After Bonferroni-Holm correction, patients with FS compared with seizure-naïve controls exhibited thinner bilateral superior temporal cortex (left 0.053 mm, p = 0.014; right 0.071 mm, p = 0.00006), thicker left lateral occipital cortex (0.052 mm, p = 0.0035), and greater left cerebellar white-matter volume (1085 mm³, p = 0.0065). These findings were not accounted for by lower MRI quality in patients with FS.

CONCLUSIONS

These results reinforce prior indications of structural neuroimaging correlates of FS and, in particular, distinguish brain morphology in FS from that in depression, anxiety, and OCD. Future work may entail comparisons with other psychiatric disorders including bipolar and schizophrenia, as well as exploration of brain structural heterogeneity within FS.

History of suicide attempts associated with the thinning right superior temporal gyrus among individuals with schizophrenia

Individuals with schizophrenia have higher rates of suicide attempts than the general population. Specific cortical abnormalities (e.g., the cortical surface area and thickness) may be associated with a history of suicide attempts. We recruited 74 individuals with schizophrenia (37 suicide attempters were individually matched with 37 non-attempters on age, sex, phase of illness, and study center) and 37 healthy volunteers. The cortical surface area and thickness data were extracted from structural MRI and compared between the groups. Suicide attempters showed significantly smaller surface areas in the whole brain (p = .028, Cohen's d = -0.54) than non-attempters. No association was found between the cortical surface area of individual brain regions and a history of suicide attempts. The mean cortical thickness did not differ significantly between the groups; however, suicide attempters demonstrated a thinner cortex in the right superior temporal gyrus (p < .001, q = 0.037, Cohen's d = -0.88). These findings indicate that a history of suicide attempts among individuals with schizophrenia is associated with a reduction in the global cortical surface area and specific cortical thinning of the right superior temporal gyrus. The morphometric alteration of the right superior temporal gyrus may represent a biomarker of suicidal behavior in individuals with schizophrenia.

Diminished frontal pole size and functional connectivity in young adults with high suicidality

BACKGROUND

Suicide rates among young people have been increasing in recent years, yet no validated methods are available for identifying those who are at greatest risk for suicide. Abnormalities in the medial prefrontal cortex have been previously observed in suicidal individuals, but confounding factors such as treatment and chronic illness may have contributed to these findings. Thus, in this study we tested whether the size of the medial prefrontal cortex is altered in suicidal young adults who have received no treatment with psychotropic medications.

METHODS

Suicidality was evaluated using the Suicide Behaviors Questionnaire-Revised (SBQ-R) and surface areas of four regions-of-interest (ROIs) within the medial prefrontal cortex were measured using magnetic resonance imaging (MRI) in a cohort of college students (n = 102). In addition, a secondary seed-based functional connectivity analysis was conducted using resting-state functional MRI data. Areas and functional connectivity of the medial prefrontal cortex of young adults with high suicidality (HS; SBQ-R score > 7; n = 20) were compared to those with low suicidality (LS; SBQ-R score = 3, n = 37).

RESULTS

Compared to the LS group, the HS group had a significantly lower surface area of the right frontal pole (p < 0.05, Bonferroni-corrected) and significantly lower functional connectivity of the right frontal pole with the bilateral inferior frontal cortex (p < 0.001, Monte-Carlo corrected).

LIMITATION

These findings require replication in a larger sample and extension in younger (adolescent) populations.

CONCLUSION

Diminished frontal pole surface area and functional connectivity may be linked to elevated levels of suicidality in young people.

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

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

Psilocybin, a Naturally Occurring Indoleamine Compound, Could Be Useful to Prevent Suicidal Behaviors

The available interventions for people who are at risk of suicide have limited efficacy. Recently, research on new mental health treatments has started to consider psychedelic compounds, particularly psilocybin, a molecule with a few thousand years of history of use in human societies. The possible effects of psilocybin on suicidal ideation and behaviors have not been specifically studied yet; however, the current knowledge on the suicidal process and the available data on es/ketamine suggest that psylocibin could be used to modulate the thoughts and behavioral patterns in individuals who are at risk of suicidal behaviors. Here, we summarize the available evidence on the possible mechanisms underlying psilocybin positive effects on suicide risk. Major pathways related to suicidal behaviors that might be modulated by psylocibin include serotonin receptors. Specifically, psylocibin directly stimulates the serotonin 2A receptor (5HT_2A), targeting the inflammatory and oxidative stress pathways and leading to a rapid increase in brain plasticity and inflammation suppression and increases in cognitive flexibility, spirituality, and empathy. We also present preliminary epidemiological data and provide a rationale for studying psilocybin in individuals with suicidal ideation or who are at risk of suicidal behaviors. This review presents a framework to understand the basis for psilocybin use in individuals who are at risk of suicidal behaviors and calls for clinical studies.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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.

Parental Education, Household Income, and Cortical Surface Area among 9-10 Years Old Children: Minorities' Diminished Returns

Introduction: Although the effects of parental education and household income on children's brain development are well established, less is known about possible variation in these effects across diverse racial and ethnic groups. According to the Minorities' Diminished Returns (MDRs) phenomenon, due to structural racism, social stratification, and residential segregation, parental educational attainment and household income show weaker effects for non-White than White children. Purpose: Built on the MDRs framework and conceptualizing race as a social rather than a biological factor, this study explored racial and ethnic variation in the magnitude of the effects of parental education and household income on children's whole-brain cortical surface area. Methods: For this cross-sectional study, we used baseline socioeconomic and structural magnetic resonance imaging (sMRI) data of the Adolescent Brain Cognitive Development (ABCD) study. Our analytical sample was 10,262 American children between ages 9 and 10. The independent variables were parental education and household income. The primary outcome was the children's whole-brain cortical surface area. Age, sex, and family marital status were covariates. Race and ethnicity were the moderators. We used mixed-effects regression models for data analysis as participants were nested within families and study sites. Results: High parental education and household income were associated with larger children's whole-brain cortical surface area. The effects of high parental education and high household income on children's whole-brain cortical surface area were modified by race. Compared to White children, Black children showed a diminished return of high parental education on the whole-brain cortical surface area when compared to White children. Asian American children showed weaker effects of household income on the whole-brain cortical surface area when compared to White children. We could not find differential associations between parental education and household income with the whole-brain cortical surface area, when compared to White children, for non-Hispanic and Hispanic children. Conclusions: The effects of parental educational attainment and household income on children's whole-brain cortical surface area are weaker in non-White than White families. Although parental education and income contribute to children's brain development, these effects are unequal across racial groups.