Hyperarousal symptoms and perceived burdensomeness interact to predict suicidal ideation among trauma-exposed individuals

Differences in intestinal bacteria in traumatic injury survivors with and without probable posttraumatic stress disorder

BACKGROUND

Posttraumatic stress disorder (PTSD) is a common consequence of traumatic injury, yet certain biological factors contributing to PTSD are poorly understood. The gut microbiome may influence mental health outcomes, but its role in heterogeneous PTSD presentations requires elucidation.

METHODS

Bacterial composition was examined in adults 2-4 years post-trauma with probable PTSD (n = 24) versus trauma-exposed controls without probable PTSD (n = 24). 16S rRNA sequencing and bioinformatic tools assessed microbial diversity and abundance. Relationships between taxa and PTSD symptom clusters were evaluated.

RESULTS

No differences were found in overall microbial community structure between groups. The probable PTSD group exhibited significantly reduced Actinobacteriota and increased Verrucomicrobiota phylum abundance compared to controls. Specific taxa showed notable inverse associations with negative mood/cognition versus hyperarousal symptoms. Prevotella and Ruminococcaceae were negatively associated with negative mood but positively associated with hyperarousal.

CONCLUSIONS

Results demonstrate microbial signatures of probable PTSD subtypes, highlighting the microbiome as a potential mediator of heterogeneous trauma psychopathology. Definition of PTSD microbial correlates provides a foundation for personalized psychobiotic interventions targeting predominant symptom profiles.

The Impact of Bullying Victimization and Sexual Orientation on the Severity of Suicidal Behavior

Background: Lesbian, gay, and bisexual youth face a disproportionate risk of suicidal ideation and attempt compared to heterosexual counterparts. Escalation from ideation to attempt can occur quickly, and youth who survive suicide attempts are likely to pursue subsequent, riskier attempts. This study examines the effects of bullying and sexual orientation on suicidal outcomes. Methods: Data came from the national, school-administered 2017 Youth Risk Behavior Survey (N = 14,765). Bivariate associations, binomial logistic regressions, and ordinal logistic regressions were performed. Results: Lesbian/gay, bisexual, and unsure youth reported greater odds of ideation and attempts compared to heterosexual youth. For ideation, increased effects were inconsistent across bullying types and significant interactions were found for bisexual youth who were bullied in school, and for lesbian/gay youth who were cyberbullied. Conclusion: These results underscore the need to understand bullying victimization for lesbian, gay, and bisexual youth. Awareness of increasing cyberbullying and creating school environments of no-bullying tolerance in the post-pandemic era are among the challenges ahead.

Toward an integrative model of transdiagnostic risk factors and suicide: A network comparison of psychiatric outpatients

Predictive models using traditional statistical methods have largely failed to describe suicide etiology. Network theory, which conceptualizes factors as mutually interacting, reinforcing elements of a complex outcome, can model relationships between transdiagnostic and neurocognitive vulnerability factors. The present study used a network approach to produce an atheoretical model of psychological factors and their interrelationships within a population of ideators and non-ideators. We developed two network models (i.e., suicidal ideators and psychiatric controls) describing the relationships between a diverse set of risk factors and symptom measures for a population of psychiatric outpatients. We compared networks using three measures of network structure (i.e., network structure invariance, global strength invariance, edge invariance) and described the differences. Network structures for ideators (N = 229) and non-ideators (N = 454) were stable and accurate. In non-ideators, cognitive-affective depression symptoms (Expected Influence [EI]: 2.06), trauma avoidance (EI: 1.08), and negative affect (EI: 0.81) were most influential to the psychological network. In ideators, cognitive-affective depression symptoms (EI: 1.77), intolerance of uncertainty-negative self-referent implications (EI: 1.29), and negative affect (EI: 1.19) were most influential. Invariance testing did not indicate significant differences in overall network structure between ideators and non-ideators (p = .111), but did indicate significant differences in node strength (p = .013). Significant differences in node EI were detected for intolerance of uncertainty-negative self-referent implications, anxiety sensitivity physical concerns, thwarted belongingness, worry, and negative affect. These findings indicated differences in network structures for suicidal psychiatric outpatients and provide crucial directions for future research on therapeutic targets for suicidal thoughts and behaviors.

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.