Connectome-based functional connectivity markers of suicide attempt

The neural connectome of suicidality in adults with mood and anxiety disorders

Although suicide risk is a major public health issue, attempts to understand the neural basis of suicidality have been limited by small sample sizes and a focus on specific psychiatric disorders. This sample comprised 579 participants, of whom 428 had a psychiatric disorder (depression, anxiety or stress-related disorder) and 151 were non-psychiatric controls. All participants underwent structured clinical interviews, including an assessment of suicidality in the past month, and completed a functional magnetic resonance imaging scan. There were 238 (41.1%) participants who met criteria for suicidality and 341 (58.9%) were non-suicidal. Task-derived functional connectivity was calculated for 436 brain regions, comprising 8 intrinsic connectivity networks. Participants who were suicidal had decreased connectivity in a network of 143 connections across 86 brain regions. This pattern was characterized primarily by decreased connectivity within the visual, somatomotor and salience networks, between these networks, and also with the default mode and limbic networks. By adopting a transdiagnostic approach with a very large sample of individuals with mood disorders, anxiety and stress and non-psychiatric participants, this study highlights the hypoconnectivity that characterizes suicidality and points to altered connectivity within and between key networks involved in emotional, sensory and cognitive processes that are implicated in suicidal risk.

A network frame offers a promising transdisciplinary tool for understanding complex health and health care system problems like suicide

As health and health care systems continue to face massive challenges from local to global well-being, understanding the processes that lead to improvement or deterioration in human health has embraced a broad range of forces from genes to national cultures. Despite the many efforts to deploy a common framework that captures diverse drivers at scale, the common missing element is the absence of a flexible mechanism that can guide research within and across levels. This hinders both the cumulation of knowledge and the development of a scientific foundation for multiplex interventions. However, studies across disciplines using a wide variety of methods and measures have converged on "connectedness" as crucial to understanding how factors operate in the health space. More formally, a focus on the critical role of the network structure and content of key elements and how they interact, rather than just on the elements themselves, offers both a generalized theory of active factors within levels and the potential to theorize interactions across levels. One critical contemporary health crisis, suicide, is deployed to illustrate the Network Embedded Symbiome Framework. The wide range of health and health care research where networks have been implicated supports its potential but also cautions against inevitable limits that will require creative theorizing and data harmonization to move forward.

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.

Aberrant connectivity in the right amygdala and right middle temporal gyrus before and after a suicide attempt: Examining markers of suicide risk

Functional neuroimaging has the potential to help identify those at risk for self-injurious thoughts and behaviors, as well as inform neurobiological mechanisms that contribute to suicide. Based on whole-brain patterns of functional connectivity, our previous work identified right amygdala and right middle temporal gyrus (MTG) connectivity patterns that differentiated Veterans with a history of a suicide attempt (SA) from a Veteran control group. In this study, we aimed to replicate and extend our previous findings by examining whether this aberrant connectivity was present prior to and after a SA. In a trauma-exposed Veteran sample (92 % male, mean age = 34), we characterized if the right amygdala and right MTG connectivity differed between a psychiatric control sample (n = 56) and an independent sample of Veterans with a history of SA (n = 17), using fMRI data before and after the SA. Right MTG and amygdala connectivity differed between Veterans with and without a history of SA (replication), while MTG connectivity also distinguished Veterans prior to engaging in a SA (extension). In a second study, neither MTG or amygdala connectivity differed between those with current suicidal ideation (n = 27) relative to matched psychiatric controls (n = 27). These results indicate a potential stable marker of suicide risk (right MTG connectivity) as well as a potential marker of acute risk of or recent SA (right amygdala connectivity) that are independent of current ideation.

Cardiovascular and metabolic health is associated with functional brain connectivity in middle-aged and older adults: Results from the Human Connectome Project-Aging study

Several cardiovascular and metabolic indicators, such as cholesterol and blood pressure have been associated with altered neural and cognitive health as well as increased risk of dementia and Alzheimer's disease in later life. In this cross-sectional study, we examined how an aggregate index of cardiovascular and metabolic risk factor measures was associated with correlation-based estimates of resting-state functional connectivity (FC) across a broad adult age-span (36-90+ years) from 930 volunteers in the Human Connectome Project Aging (HCP-A). Increased (i.e., worse) aggregate cardiometabolic scores were associated with reduced FC globally, with especially strong effects in insular, medial frontal, medial parietal, and superior temporal regions. Additionally, at the network-level, FC between core brain networks, such as default-mode and cingulo-opercular, as well as dorsal attention networks, showed strong effects of cardiometabolic risk. These findings highlight the lifespan impact of cardiovascular and metabolic health on whole-brain functional integrity and how these conditions may disrupt higher-order network integrity.

Cortical hierarchy disorganization in major depressive disorder and its association with suicidality

Objectives

To explore the suicide risk-specific disruption of cortical hierarchy in major depressive disorder (MDD) patients with diverse suicide risks.

Methods

Ninety-two MDD patients with diverse suicide risks and 38 matched controls underwent resting-state functional MRI. Connectome gradient analysis and stepwise functional connectivity (SFC) analysis were used to characterize the suicide risk-specific alterations of cortical hierarchy in MDD patients.

Results

Relative to controls, patients with suicide attempts (SA) had a prominent compression from the sensorimotor system; patients with suicide ideations (SI) had a prominent compression from the higher-level systems; non-suicide patients had a compression from both the sensorimotor system and higher-level systems, although it was less prominent relative to SA and SI patients. SFC analysis further validated this depolarization phenomenon.

Conclusion

This study revealed MDD patients had suicide risk-specific disruptions of cortical hierarchy, which advance our understanding of the neuromechanisms of suicidality in MDD patients.

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

BACKGROUND

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

METHODS

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

RESULTS

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

LIMITATIONS

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

CONCLUSIONS

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

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

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

An executive function subtype of PTSD with unique neural markers and clinical trajectories

Previous work identified a cognitive subtype of PTSD with impaired executive function (i.e., impaired EF-PTSD subtype) and aberrant resting-state functional connectivity between frontal parietal control (FPCN) and limbic (LN) networks. To better characterize this cognitive subtype of PTSD, this study investigated (1) alterations in specific FPCN and LN subnetworks and (2) chronicity of PTSD symptoms. In a post-9/11 veteran sample (N = 368, 89% male), we identified EF subgroups using a standardized neuropsychological battery and a priori cutoffs for impaired, average, and above-average EF performance. Functional connectivity between two subnetworks of the FPCN and three subnetworks of the LN was assessed using resting-state fMRI (n = 314). PTSD chronicity over a 1-2-year period was assessed using a reliable change index (n = 175). The impaired EF-PTSD subtype had significantly reduced negative functional connectivity between the FPCN subnetwork involved in top-down control of emotion and two LN subnetworks involved in learning/memory and social/emotional processing. This impaired EF-PTSD subtype had relatively chronic PTSD, while those with above-average EF and PTSD displayed greater symptom reduction. Lastly, FPCN-LN subnetworks partially mediated the relationship between EF and PTSD chronicity (n = 121). This study reveals (1) that an impaired EF-PTSD subtype has a specific pattern of FPCN-LN subnetwork connectivity, (2) a novel above-average EF-PTSD subtype displays reduced PTSD chronicity, and (3) both cognitive and neural functioning predict PTSD chronicity. The results indicate a need to investigate how individuals with this impaired EF-PTSD subtype respond to treatment, and how they might benefit from personalized and novel approaches that target these neurocognitive systems.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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